The science papers I've read

Today I read a paper titled “Progressive Gaussian Filtering”

Fuck me! Nice feedback filtering and sampling system!

The abstract is:

In this paper, we propose a progressive Bayesian procedure, where the measurement information is continuously included into the given prior estimate (although we perform observations at discrete time steps). The key idea is to derive a system of ordinary first-order differential equations (ODE) by employing a new coupled density representation comprising a Gaussian density and its Dirac Mixture approximation. The ODE is used for continuously tracking the true non-Gaussian posterior by its best matching Gaussian approximation. The performance of the new filter is evaluated in comparison with state-of-the-art filters by means of a canonical benchmark example, the discrete-time cubic sensor problem. 

Unbounded Human Learning: Optimal Scheduling for Spaced Repetition

Today I read a paper titled “Unbounded Human Learning: Optimal Scheduling for Spaced Repetition”

I like the fact that there is an empirical evaluation of the results against an actual audience and not just merely conjecture. The queuing implementation is useful. My concern is with “human boredom” that could arise from a badly tuned, automatic system (though no worse than a badly tuned system designed by a human). We want to help the subjects memorise what they need, but we also need to keep feeding them novel, i.e. new, knowledge to keep them engaged.

The abstract is:

In the study of human learning, there is broad evidence that our ability to retain information improves with repeated exposure and decays with delay since last exposure. This plays a crucial role in the design of educational software, leading to a trade-off between teaching new material and reviewing what has already been taught. A common way to balance this trade-off is spaced repetition, which uses periodic review of content to improve long-term retention. Though spaced repetition is widely used in practice, e.g., in electronic flashcard software, there is little formal understanding of the design of these systems. Our paper addresses this gap in three ways. First, we mine log data from spaced repetition software to establish the functional dependence of retention on reinforcement and delay. Second, we use this memory model to develop a stochastic model for spaced repetition systems. We propose a queueing network model of the Leitner system for reviewing flashcards, along with a heuristic approximation that admits a tractable optimization problem for review scheduling. Finally, we empirically evaluate our queueing model through a Mechanical Turk experiment, verifying a key qualitative prediction of our model: the existence of a sharp phase transition in learning outcomes upon increasing the rate of new item introductions. 

Design of an Agent for Answering Back in Smart Phones

Today I read a published paper titled “Design of an Agent for Answering Back in Smart Phones”

Shallow fluff with obvious solutions to obvious problems.

The abstract is:

The objective of the paper is to design an agent which provides efficient response to the caller when a call goes unanswered in smartphones. The agent provides responses through text messages, email etc stating the most likely reason as to why the callee is unable to answer a call. Responses are composed taking into consideration the importance of the present call and the situation the callee is in at the moment like driving, sleeping, at work etc. The agent makes decisons in the compostion of response messages based on the patterns it has come across in the learning environment. Initially the user helps the agent to compose response messages. The agent associates this message to the percept it recieves with respect to the environment the callee is in. The user may thereafter either choose to make to response system automatic or choose to recieve suggestions from the agent for responses messages and confirm what is to be sent to the caller.

Study of Gesture Recognition methods and augmented reality

Today I read a paper titled “Study of Gesture Recognition methods and augmented reality”

Difficult to read due to the stilted language but not due to the content. The content of the study was not that revealing in terms of new knowledge. I guess it would be useful if I wasn’t already familiar with the subject and just need a quick overview.

The abstract is:

With the growing technology, we humans always need something that stands out from the other thing. Gestures are most desirable source to Communicate with the Machines. Human Computer Interaction finds its importance when it comes to working with the Human gestures to control the computer applications. Usually we control the applications using mouse, keyboard, laser pointers etc. but, with the recent advent in the technology it has even left behind their usage by introducing more efficient techniques to control applications. There are many Gesture Recognition techniques that have been implemented using image processing in the past. However recognizing the gestures in the noisy background has always been a difficult task to achieve. In the proposed system, we are going to use one such technique called Augmentation in Image processing to control Media Player. We will recognize Gestures using which we are going to control the operations on Media player. Augmentation usually is one step ahead when it comes to virtual reality. It has no restrictions on the background. Moreover it also does not rely on certain things like gloves, color pointers etc. for recognizing the gesture. This system mainly appeals to those users who always looks out for a better option that makes their interaction with computer more simpler or easier.

Unsupervised Incremental Learning and Prediction of Music Signals

Today I read a paper titled “Unsupervised Incremental Learning and Prediction of Music Signals”

Part of some personal research work I am doing with music generation software.

The abstract is:

A system is presented that segments, clusters and predicts musical audio in an unsupervised manner, adjusting the number of (timbre) clusters instantaneously to the audio input. A sequence learning algorithm adapts its structure to a dynamically changing clustering tree. The flow of the system is as follows: 1) segmentation by onset detection, 2) timbre representation of each segment by Mel frequency cepstrum coefficients, 3) discretization by incremental clustering, yielding a tree of different sound classes (e.g. instruments) that can grow or shrink on the fly driven by the instantaneous sound events, resulting in a discrete symbol sequence, 4) extraction of statistical regularities of the symbol sequence, using hierarchical N-grams and the newly introduced conceptual Boltzmann machine, and 5) prediction of the next sound event in the sequence. The system’s robustness is assessed with respect to complexity and noisiness of the signal. Clustering in isolation yields an adjusted Rand index (ARI) of 82.7% / 85.7% for data sets of singing voice and drums. Onset detection jointly with clustering achieve an ARI of 81.3% / 76.3% and the prediction of the entire system yields an ARI of 27.2% / 39.2%.

Combining Brain-Computer Interfaces and Haptics: Detecting Mental Workload to Adapt Haptic Assistance

Today I read a published paper titled “Combining Brain-Computer Interfaces and Haptics: Detecting Mental Workload to Adapt Haptic Assistance”

I think application of an assistance device in the medical field would be mind blowing (no pun intended). A device that could help a tired doctor diagnose a patient or a surgeon complete an operation.

Or in semi-autonomous vehicles when detecting driver fatigue. Hell, even if software development when you are really deep in the code.

The abstract is:

 In this paper we introduce the combined use of Brain-Computer Interfaces (BCI) and Haptic interfaces. We propose to adapt haptic guides based on the mental activity measured by a BCI system. This novel approach is illustrated within a proof-of-concept system: haptic guides are toggled during a path-following task thanks to a mental workload index provided by a BCI. The aim of this system is to provide haptic assistance only when the user’s brain activity reflects a high mental workload. A user study conducted with 8 participants shows that our proof-of-concept is operational and exploitable. Results show that activation of haptic guides occurs in the most difficult part of the path-following task. Moreover it allows to increase task performance by 53% by activating assistance only 59% of the time. Taken together, these results suggest that BCI could be used to determine when the user needs assistance during haptic interaction and to enable haptic guides accordingly. 

Guaranteed bounds on the Kullback-Leibler divergence of univariate mixtures using piecewise log-sum-exp inequalities

Today I read a published paper titled “Guaranteed bounds on the Kullback-Leibler divergence of univariate mixtures using piecewise log-sum-exp inequalities”

Some of the math was a bit obtuse, but a useful method that could be used for fingerprinting malware, tagging and label similar images using information divergence. The fact that this technique does not require a Monte-Carlo simulation is significant.

The abstract is:
The Kullback-Leibler divergence between two mixture models is a core primitive in many signal processing tasks. Since the Kullback-Leibler divergence of mixtures does not admit closed-form formula, it is in practice either estimated using costly Monte-Carlo stochastic integration or approximated using various techniques. We present a fast and generic method that builds algorithmically closed-form lower and upper bounds on the entropy, the cross-entropy and the Kullback-Leibler divergence of mixtures. We illustrate the versatile method by reporting on our experiments for approximating the Kullback-Leibler divergence between univariate exponential mixtures, Gaussian mixtures and Rayleigh mixtures.

Today I read a published paper titled “Virtual Windshields: Merging Reality and Digital Content to Improve the Driving Experience”

We are barely on the cusp of driver assistance devices in vehicles today. If full autonomous vehicles don’t get here first (I suspect they will for 99% of all daily driving), augmented reality and digital windscreens are a game changer.

The abstract is:

In recent years, the use of the automobile as the primary mode of transportation has been increasing and driving has become an important part of daily life. Driving is a multi-sensory experience as drivers rely on their senses to provide them with important information. In a vehicular context human senses are all too often limited and obstructed. Today, road accidents constitute the eighth leading cause of death. The escalation of technology has propelled new ways in which driver’s senses may be augmented. The enclosed aspect of a car, allied with the configuration of the controls and displays directed towards the driver, offer significant advantages for augmented reality (AR) systems when considering the amount of immersion it can provide to the user. In addition, the inherent mobility and virtually unlimited power autonomy transform cars into perfect mobile computing platforms. However, automobiles currently present limited network connectivity and thus the created augmented objects are merely providing information captured by in-vehicle sensors, cameras and other databases. By combining the new paradigm of Vehicular Ad Hoc Networking (VANET) with AR human machine interfaces, we show that it is possible to design novel cooperative Advanced Driver Assistance Systems (ADAS), that base the creation of AR content on the information collected from neighbouring vehicles or roadside infrastructures. As such we implement prototypes of both visual and acoustic AR systems, which can significantly improve the driving experience. We believe our results contribute to the formulation of a vision where the vehicle is perceived as an extension of the body which permeates the human senses to the world outside the vessel, where the car is used as a better, multi-sensory immersive version of a mobile phone that integrates touch, vision and sound enhancements, leveraging unique properties of VANET.

Egocentric vision IT technologies for Alzheimer disease assessment and studies

Today I read a published paper titled “Egocentric vision IT technologies for Alzheimer disease assessment and studies”

Sort of a SenseCam on steroids with applications towards helping Alzheimer’s sufferers. From what I read I believe this work is kind of early days yet, but it could hold great promise.

The abstract is:

Egocentric vision technology consists in capturing the actions of persons from their own visual point of view using wearable camera sensors. We apply this new paradigm to instrumental activities monitoring with the objective of providing new tools for the clinical evaluation of the impact of the disease on persons with dementia. In this paper, we introduce the current state of the development of this technology and focus on two technology modules: automatic location estimation and visual saliency estimation for content interpretation.

Reconstructing Self Organizing Maps as Spider Graphs for better visual interpretation of large unstructured datasets

Today I read a published paper “Reconstructing Self Organizing Maps as Spider Graphs for better visual interpretation of large unstructured datasets”

The abstract is:

Self-Organizing Maps (SOM) are popular unsupervised artificial neural network used to reduce dimensions and visualize data. Visual interpretation from Self-Organizing Maps (SOM) has been limited due to grid approach of data representation, which makes inter-scenario analysis impossible. The paper proposes a new way to structure SOM. This model reconstructs SOM to show strength between variables as the threads of a cobweb and illuminate inter-scenario analysis. While Radar Graphs are very crude representation of spider web, this model uses more lively and realistic cobweb representation to take into account the difference in strength and length of threads. This model allows for visualization of highly unstructured dataset with large number of dimensions, common in Bigdata sources.

Human Pose Estimation from RGB Input Using Synthetic Training Data

Today I read a published paper “Human Pose Estimation from RGB Input Using Synthetic Training Data”

The abstract is:

We address the problem of estimating the pose of humans using RGB image input. More specifically, we are using a random forest classifier to classify pixels into joint-based body part categories, much similar to the famous Kinect pose estimator [11], [12]. However, we are using pure RGB input, i.e. no depth. Since the random forest requires a large number of training examples, we are using computer graphics generated, synthetic training data. In addition, we assume that we have access to a large number of real images with bounding box labels, extracted for example by a pedestrian detector or a tracking system. We propose a new objective function for random forest training that uses the weakly labeled data from the target domain to encourage the learner to select features that generalize from the synthetic source domain to the real target domain. We demonstrate on a publicly available dataset [6] that the proposed objective function yields a classifier that significantly outperforms a baseline classifier trained using the standard entropy objective [10].

Smart Context-aware Rejuvenation of Engagement on Urban Ambient Augmented Things

Today I read a published paper “Smart Context-aware Rejuvenation of Engagement on Urban Ambient Augmented Things”

The abstract is:

The concern over global urbanization trend imposes smart-city as enabling information and communication technology (ICT) to improve urban governance. However, the light trance on better living space is stimulated by socioeconomic impact of escalated senior generation. Hence, ambient assisted living (AAL) emerges for the autonomous provisioning of pervasive things or objects from relevant perturbation for advanced scientific instrumentation. Meanwhile, citizens are observed in being transfixed by lively stimuli of monotonous urban events with the advent of virtual reality or augmented things. Thus, due to the involvement of situation-awareness or contextualization, engagement/participation information as a utility promises to improve urban experience. However, it is complex to grapple meaningful concepts due to personalization obstacles, such as citizen psychology, information gap, service-visualization. Moreover, recommended practices deficit adaptation to monochromatic choice, disparate impairments, mobility and annotation-richness in urban space. Hence, rejuvenation of engagement relates to monitoring and quantification of ‘service consumption and graceful degradation’ of experience. However, paramount challenges are imposed on this stipulation, such as, unobservability, independence and composite relationship of contexts. Therefore, a parametric Bayesian based model is envisioned to address observability and scalability of contexts and its conjugal relationship with engagement. Last but not the least, systematic framework is demonstrated, which pinpoints key goals of context-aware engagement from participants’ opinions, usages and feed-backs.

Operation of a Brain-Computer Interface Walking Simulator by Users with Spinal Cord Injury

Today I read a published paper “Operation of a Brain-Computer Interface Walking Simulator by Users with Spinal Cord Injury”

The abstract is:

Background: Spinal cord injury (SCI) can leave the affected individuals unable to ambulate. Since there are no restorative treatments for SCI, novel approaches such as brain-controlled prostheses have been sought. Our recent studies show that a brain-computer interface (BCI) can be used to control ambulation within a virtual reality environment (VRE), suggesting that a BCI-controlled lower extremity prosthesis for ambulation may be feasible. However, the operability of our BCI has not been tested in a SCI population. Methods: Five subjects with paraplegia or tetraplegia due to SCI underwent a 10-min training session in which they alternated between kinesthetic motor imagery (KMI) of idling and walking while their electroencephalogram (EEG) were recorded. Subjects then performed a goal-oriented online task, where they utilized KMI to control the linear ambulation of an avatar and make 10 sequential stops at designated points within the VRE. Multiple online trials were performed over 5 experimental days. Results: Classification accuracy of idling and walking was estimated offline and ranged from 60.5% (p=0.0176) to 92.3% (p=1.36*10^-20) across subjects and days. In the online task, all subjects achieved purposeful control with an average performance of 7.4 +/- 2.3 successful stops in 273 +/- 51 sec (p<0.01). All subjects maintained purposeful control throughout the study, and their online performances improved over time. Conclusions: The results demonstrate that SCI subjects can purposefully operate a self-paced BCI walking simulator to complete a goal-oriented ambulation task. The operation of this BCI system requires short training, is intuitive, and robust against subject-to-subject and day-to-day neurophysiological variations. These findings indicate that BCI-controlled lower extremity prostheses for gait rehabilitation or restoration after SCI may be feasible in the future.

Multi-robot Cooperative Box-pushing problem using Multi-objective Particle Swarm Optimization Technique

Today I read a published paper “Multi-robot Cooperative Box-pushing problem using Multi-objective Particle Swarm Optimization Technique”

The abstract is:

The present work provides a new approach to solve the well-known multi-robot co-operative box pushing problem as a multi objective optimization problem using modified Multi-objective Particle Swarm Optimization. The method proposed here allows both turning and translation of the box, during shift to a desired goal position. We have employed local planning scheme to determine the magnitude of the forces applied by the two mobile robots perpendicularly at specific locations on the box to align and translate it in each distinct step of motion of the box, for minimization of both time and energy. Finally the results are compared with the results obtained by solving the same problem using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed scheme is found to give better results compared to NSGA-II.

Breaking the Barriers to True Augmented Reality

Today I read a published paper “Breaking the Barriers to True Augmented Reality”

The abstract is:

In recent years, Augmented Reality (AR) and Virtual Reality (VR) have gained considerable commercial traction, with Facebook acquiring Oculus VR for \$2 billion, Magic Leap attracting more than \$500 million of funding, and Microsoft announcing their HoloLens head-worn computer. Where is humanity headed: a brave new dystopia-or a paradise come true? In this article, we present discussions, which started at the symposium “Making Augmented Reality Real”, held at Nara Institute of Science and Technology in August 2014. Ten scientists were invited to this three-day event, which started with a full day of public presentations and panel discussions (video recordings are available at the event web page), followed by two days of roundtable discussions addressing the future of AR and VR.

Data-Driven Shape Analysis and Processing

Today I read a published paper “Data-Driven Shape Analysis and Processing”

The abstract is:

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. We provide an overview of the main concepts and components of these techniques, and discuss their application to shape classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis, through reviewing the literature and relating the existing works with both qualitative and numerical comparisons. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.

Mobile Augmented Reality Applications to Discover New Environments

Today I read a published paper “Mobile Augmented Reality Applications to Discover New Environments”

The abstract is:

Although man has become sedentary over time, his wish to travel the world remains as strong as ever. The aim of this paper is to show how techniques based on imagery and Augmented Reality (AR) can prove to be of great help when discovering a new urban environment and observing the evolution of the natural environment. The study’s support is naturally the Smartphone which in just a few years has become our most familiar device, which we take with us practically everywhere we go in our daily lives.

Visualization of Large Volumetric Multi-Channel Microscopy Data Streams on Standard PCs

Today I read a published paper “Visualization of Large Volumetric Multi-Channel Microscopy Data Streams on Standard PCs”

The abstract is:

Visualization of multi-channel microscopy data plays a vital role in biological research. With the ever-increasing resolution of modern microscopes the data set size of the scanned specimen grows steadily. On commodity hardware this size easily exceeds the available main memory and the even more limited GPU memory. Common volume rendering techniques require the entire data set to be present in the GPU memory. Existing out-of-core rendering approaches for large volume data sets either are limited to single-channel volumes, or require a computer cluster, or have long preprocessing times. Results: We introduce a ray-casting technique for rendering large volumetric multi-channel microscopy data streams on commodity hardware. The volumetric data is managed at different levels of detail by an octree structure. In contrast to previous octree-based techniques, the octree is built incrementally and therefore supports streamed microscopy data as well as data set sizes exceeding the available main memory. Furthermore, our approach allows the user to interact with the partially rendered data set at all stages of the octree construction. After a detailed description of our method, we present performance results for different multi-channel data sets with a size of up to 24 GB on a standard desktop PC. Conclusions: Our rendering technique allows biologists to visualize their scanned specimen on their standard desktop computers without high-end hardware requirements. Furthermore, the user can interact with the data set during the initial loading to explore the already loaded parts, change rendering parameters like color maps or adjust clipping planes. Thus, the time of biologists being idle is reduced. Also, streamed data can be visualized to detect and stop flawed scans early during the scan process.

Planning Random path distributions for ambush games in unstructured environments

Today I read a published paper “Planning Random path distributions for ambush games in unstructured environments”

The abstract is:

Operating vehicles in adversarial environments require non-conventional planning techniques. A two-player, zero-sum non-cooperative game is introduced, which is solved via a linear program. An extension is proposed to construct networks displaying good representations of the environment characteristics, while offering acceptable results for the technique used. Sensitivity of the solution to the LP solver algorithm is identified. The performances of the planner are finally assessed by comparison with those of conventional planners. Results are used to formulate secondary objectives to the problem.

Forward and Inverse Kinematics Seamless Matching Using Jacobian

Today I read a published paper “Forward and Inverse Kinematics Seamless Matching Using Jacobian”

The abstract is:

In this paper the problem of matching Forward Kinematics (FK) motion of a 3 Dimensional (3D) joint chain to the Inverse Kinematics (IK) movement and vice versa has been addressed. The problem lies at the heart of animating a 3D character having controller and manipulator based rig for animation within any 3D modeling and animation software. The seamless matching has been achieved through the use of pseudo-inverse of Jacobian Matrix. The Jacobian Matrix is used to determine the rotation values of each joint of character body part such as arms, between the inverse kinematics and forward kinematics motion. Then moving the corresponding kinematic joint system to the desired place, automatically eliminating the jumping or popping effect which would reduce the complexity of the system.

Efficient Hand Articulations Tracking using Adaptive Hand Model and Depth map

Today I read a published paper “Efficient Hand Articulations Tracking using Adaptive Hand Model and Depth map”

The abstract is:

Real-time hand articulations tracking is important for many applications such as interacting with virtual / augmented reality devices or tablets. However, most of existing algorithms highly rely on expensive and high power-consuming GPUs to achieve real-time processing. Consequently, these systems are inappropriate for mobile and wearable devices. In this paper, we propose an efficient hand tracking system which does not require high performance GPUs. In our system, we track hand articulations by minimizing discrepancy between depth map from sensor and computer-generated hand model. We also initialize hand pose at each frame using finger detection and classification. Our contributions are: (a) propose adaptive hand model to consider different hand shapes of users without generating personalized hand model; (b) improve the highly efficient frame initialization for robust tracking and automatic initialization; (c) propose hierarchical random sampling of pixels from each depth map to improve tracking accuracy while limiting required computations. To the best of our knowledge, it is the first system that achieves both automatic hand model adjustment and real-time tracking without using GPUs.

Low-cost Augmented Reality prototype for controlling network devices

Today I read a published paper “Low-cost Augmented Reality prototype for controlling network devices”

The abstract is:

With the evolution of mobile devices, and smart-phones in particular, comes the ability to create new experiences that enhance the way we see, interact, and manipulate objects, within the world that surrounds us. It is now possible to blend data from our senses and our devices in numerous ways that simply were not possible before using Augmented Reality technology. In a near future, when all of the office devices as well as your personal electronic gadgets are on a common wireless network, operating them using a universal remote controller would be possible. This paper presents an off-the-shelf, low-cost prototype that leverages the Augmented Reality technology to deliver a novel and interactive way of operating office network devices around using a mobile device. We believe this type of system may provide benefits to controlling multiple integrated devices and visualizing interconnectivity or utilizing visual elements to pass information from one device to another, or may be especially beneficial to control devices when interacting with them physically may be difficult or pose danger or harm.

Free-body Gesture Tracking and Augmented Reality Improvisation for Floor and Aerial Dance

Today I read a published paper “Free-body Gesture Tracking and Augmented Reality Improvisation for Floor and Aerial Dance”

The abstract is:

This paper describes an updated interactive performance system for floor and Aerial Dance that controls visual and sonic aspects of the presentation via a depth sensing camera (MS Kinect). In order to detect, measure and track free movement in space, 3 degree of freedom (3-DOF) tracking in space (on the ground and in the air) is performed using IR markers with a method for multi target tracking capabilities added and described in detail. An improved gesture tracking and recognition system, called Action Graph (AG), is described in the paper. Action Graph uses an efficient incremental construction from a single long sequence of movement features and automatically captures repeated sub-segments in the movement from start to finish with no manual interaction needed with other advanced capabilities discussed as well. By using the new model for the gesture we can unify an entire choreography piece by dynamically tracking and recognizing gestures and sub-portions of the piece. This gives the performer the freedom to improvise based on a set of recorded gestures/portions of the choreography and have the system dynamically respond in relation to the performer within a set of related rehearsed actions, an ability that has not been seen in any other system to date.

Free-body Gesture Tracking and Augmented Reality Improvisation for Floor and Aerial Dance

Today I read a published paper titled “Free-body Gesture Tracking and Augmented Reality Improvisation for Floor and Aerial Dance”

Thought it was a rather novel application for a Microsoft Kinect. Not sure if I will ever apply any of the content to my own work. But still an interesting read.

The abstract is:

This paper describes an updated interactive performance system for floor and Aerial Dance that controls visual and sonic aspects of the presentation via a depth sensing camera (MS Kinect). In order to detect, measure and track free movement in space, 3 degree of freedom (3-DOF) tracking in space (on the ground and in the air) is performed using IR markers with a method for multi target tracking capabilities added and described in detail. An improved gesture tracking and recognition system, called Action Graph (AG), is described in the paper. Action Graph uses an efficient incremental construction from a single long sequence of movement features and automatically captures repeated sub-segments in the movement from start to finish with no manual interaction needed with other advanced capabilities discussed as well. By using the new model for the gesture we can unify an entire choreography piece by dynamically tracking and recognizing gestures and sub-portions of the piece. This gives the performer the freedom to improvise based on a set of recorded gestures/portions of the choreography and have the system dynamically respond in relation to the performer within a set of related rehearsed actions, an ability that has not been seen in any other system to date.

Improving Perceptual Color Difference using Basic Color Terms

Today I read a published paper “Improving Perceptual Color Difference using Basic Color Terms”

The abstract is:

We suggest a new color distance based on two observations. First, perceptual color differences were designed to be used to compare very similar colors. They do not capture human perception for medium and large color differences well. Thresholding was proposed to solve the problem for large color differences, i.e. two totally different colors are always the same distance apart. We show that thresholding alone cannot improve medium color differences. We suggest to alleviate this problem using basic color terms. Second, when a color distance is used for edge detection, many small distances around the just noticeable difference may account for false edges. We suggest to reduce the effect of small distances.

Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier

Today I read a published paper titled “Graphic Symbol Recognition using Graph Based Signature and Bayesian  Network Classifier”

Interesting combination of a relational graph and a Bayesian network to recognise non-alphanumeric symbols in technical documents. As this is a reasonably hard problem to solve (or it was when I was doing that sort of thing about 20 years ago) it is encouraging to read new approaches (new for me anyway) to the problem. I wish the recognition rates (acknowledged in the paper) were a little higher.

The abstract:

We present a new approach for recognition of complex graphic symbols in technical documents. Graphic symbol recognition is a well known challenge in the field of document image analysis and is at heart of most graphic recognition systems. Our method uses structural approach for symbol representation and statistical classifier for symbol recognition. In our system we represent symbols by their graph based signatures: a graphic symbol is vectorized and is converted to an attributed relational graph, which is used for computing a feature vector for the symbol. This signature corresponds to geometry and topology of the symbol. We learn a Bayesian network to encode joint probability distribution of symbol signatures and use it in a supervised learning scenario for graphic symbol recognition. We have evaluated our method on synthetically deformed and degraded images of pre-segmented 2D architectural and electronic symbols from GREC databases and have obtained encouraging recognition rates. 

Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier

Today I read a published paper “Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier”

The abstract is:

We present a new approach for recognition of complex graphic symbols in technical documents. Graphic symbol recognition is a well known challenge in the field of document image analysis and is at heart of most graphic recognition systems. Our method uses structural approach for symbol representation and statistical classifier for symbol recognition. In our system we represent symbols by their graph based signatures: a graphic symbol is vectorized and is converted to an attributed relational graph, which is used for computing a feature vector for the symbol. This signature corresponds to geometry and topology of the symbol. We learn a Bayesian network to encode joint probability distribution of symbol signatures and use it in a supervised learning scenario for graphic symbol recognition. We have evaluated our method on synthetically deformed and degraded images of pre-segmented 2D architectural and electronic symbols from GREC databases and have obtained encouraging recognition rates.

Autonomous Vehicles Need Experimental Ethics: Are We Ready for Utilitarian Cars?

Today I read a published paper “Autonomous Vehicles Need Experimental Ethics: Are We Ready for Utilitarian Cars?”

The abstract is:

The wide adoption of self-driving, Autonomous Vehicles (AVs) promises to dramatically reduce the number of traffic accidents. Some accidents, though, will be inevitable, because some situations will require AVs to choose the lesser of two evils. For example, running over a pedestrian on the road or a passer-by on the side; or choosing whether to run over a group of pedestrians or to sacrifice the passenger by driving into a wall. It is a formidable challenge to define the algorithms that will guide AVs confronted with such moral dilemmas. In particular, these moral algorithms will need to accomplish three potentially incompatible objectives: being consistent, not causing public outrage, and not discouraging buyers. We argue to achieve these objectives, manufacturers and regulators will need psychologists to apply the methods of experimental ethics to situations involving AVs and unavoidable harm. To illustrate our claim, we report three surveys showing that laypersons are relatively comfortable with utilitarian AVs, programmed to minimize the death toll in case of unavoidable harm. We give special attention to whether an AV should save lives by sacrificing its owner, and provide insights into (i) the perceived morality of this self-sacrifice, (ii) the willingness to see this self-sacrifice being legally enforced, (iii) the expectations that AVs will be programmed to self-sacrifice, and (iv) the willingness to buy self-sacrificing AVs.

Applications and a Three-dimensional Desktop Environment for an Immersive Virtual Reality System

Today I read a published paper “Applications and a Three-dimensional Desktop Environment for an Immersive Virtual Reality System”

The abstract is:

We developed an application launcher called Multiverse for scientific visualizations in a CAVE-type virtual reality (VR) system. Multiverse can be regarded as a type of three-dimensional (3D) desktop environment. In Multiverse, a user in a CAVE room can browse multiple visualization applications with 3D icons and explore movies that float in the air. Touching one of the movies causes “teleportation” into the application’s VR space. After analyzing the simulation data using the application, the user can jump back into Multiverse’s VR desktop environment in the CAVE.

Improving Big Data Visual Analytics with Interactive Virtual Reality

Today I read a published paper “Improving Big Data Visual Analytics with Interactive Virtual Reality”

The abstract is:

For decades, the growth and volume of digital data collection has made it challenging to digest large volumes of information and extract underlying structure. Coined ‘Big Data’, massive amounts of information has quite often been gathered inconsistently (e.g from many sources, of various forms, at different rates, etc.). These factors impede the practices of not only processing data, but also analyzing and displaying it in an efficient manner to the user. Many efforts have been completed in the data mining and visual analytics community to create effective ways to further improve analysis and achieve the knowledge desired for better understanding. Our approach for improved big data visual analytics is two-fold, focusing on both visualization and interaction. Given geo-tagged information, we are exploring the benefits of visualizing datasets in the original geospatial domain by utilizing a virtual reality platform. After running proven analytics on the data, we intend to represent the information in a more realistic 3D setting, where analysts can achieve an enhanced situational awareness and rely on familiar perceptions to draw in-depth conclusions on the dataset. In addition, developing a human-computer interface that responds to natural user actions and inputs creates a more intuitive environment. Tasks can be performed to manipulate the dataset and allow users to dive deeper upon request, adhering to desired demands and intentions. Due to the volume and popularity of social media, we developed a 3D tool visualizing Twitter on MIT’s campus for analysis. Utilizing emerging technologies of today to create a fully immersive tool that promotes visualization and interaction can help ease the process of understanding and representing big data.

Dynamic behavior analysis for a six axis industrial machining robot

Today I read a published paper “Dynamic behavior analysis for a six axis industrial machining robot”

The abstract is:

The six axis robots are widely used in automotive industry for their good repeatability (as defined in the ISO92983) (painting, welding, mastic deposition, handling etc.). In the aerospace industry, robot starts to be used for complex applications such as drilling, riveting, fiber placement, NDT, etc. Given the positioning performance of serial robots, precision applications require usually external measurement device with complexes calibration procedure in order to reach the precision needed. New applications in the machining field of composite material (aerospace, naval, or wind turbine for example) intend to use off line programming of serial robot without the use of calibration or external measurement device. For those applications, the position, orientation and path trajectory precision of the tool center point of the robot are needed to generate the machining operation. This article presents the different conditions that currently limit the development of robots in robotic machining applications. We analyze the dynamical behavior of a robot KUKA KR240-2 (located at the University of Bordeaux 1) equipped with a HSM Spindle (42000 rpm, 18kW). This analysis is done in three stages. The first step is determining the self-excited frequencies of the robot structure for three different configurations of work. The second phase aims to analyze the dynamical vibration of the structure as the spindle is activated without cutting. The third stage consists of vibration analysis during a milling operation.

Touch-less Interactive Augmented Reality Game on Vision Based Wearable Device

Today I read a published paper “Touch-less Interactive Augmented Reality Game on Vision Based Wearable Device”

The abstract is:

There is an increasing interest in creating pervasive games based on emerging interaction technologies. In order to develop touch-less, interactive and augmented reality games on vision-based wearable device, a touch-less motion interaction technology is designed and evaluated in this work. Users interact with the augmented reality games with dynamic hands/feet gestures in front of the camera, which triggers the interaction event to interact with the virtual object in the scene. Three primitive augmented reality games with eleven dynamic gestures are developed based on the proposed touch-less interaction technology as proof. At last, a comparing evaluation is proposed to demonstrate the social acceptability and usability of the touch-less approach, running on a hybrid wearable framework or with Google Glass, as well as workload assessment, user’s emotions and satisfaction.

Today I read a published paper titled “Coordination Games on Graphs”

Nothing to add. I need to dwell on it. Just knowledge for the sake of it.

The abstract is:

We introduce natural strategic games on graphs, which capture the idea of coordination in a local setting. We show that these games have an exact potential and have strong equilibria when the graph is a pseudoforest. We also exhibit some other classes of graphs for which a strong equilibrium exists. However, in general strong equilibria do not need to exist. Further, we study the (strong) price of stability and anarchy. Finally, we consider the problems of computing strong equilibria and of determining whether a joint strategy is a strong equilibrium.

Coordination Games on Graphs

Today I read a published paper “Coordination Games on Graphs”

The abstract is:

We introduce natural strategic games on graphs, which capture the idea of coordination in a local setting. We show that these games have an exact potential and have strong equilibria when the graph is a pseudoforest. We also exhibit some other classes of graphs for which a strong equilibrium exists. However, in general strong equilibria do not need to exist. Further, we study the (strong) price of stability and anarchy. Finally, we consider the problems of computing strong equilibria and of determining whether a joint strategy is a strong equilibrium.

Multi-agent Path Planning and Network Flow

Today I read a published paper “Multi-agent Path Planning and Network Flow”

The abstract is:

This paper connects multi-agent path planning on graphs (roadmaps) to network flow problems, showing that the former can be reduced to the latter, therefore enabling the application of combinatorial network flow algorithms, as well as general linear program techniques, to multi-agent path planning problems on graphs. Exploiting this connection, we show that when the goals are permutation invariant, the problem always has a feasible solution path set with a longest finish time of no more than $n + V – 1$ steps, in which $n$ is the number of agents and $V$ is the number of vertices of the underlying graph. We then give a complete algorithm that finds such a solution in $O(nVE)$ time, with $E$ being the number of edges of the graph. Taking a further step, we study time and distance optimality of the feasible solutions, show that they have a pairwise Pareto optimal structure, and again provide efficient algorithms for optimizing two of these practical objectives.

Markerless Motion Capture in the Crowd

Today I read a published paper “Markerless Motion Capture in the Crowd”

The abstract is:

This work uses crowdsourcing to obtain motion capture data from video recordings. The data is obtained by information workers who click repeatedly to indicate body configurations in the frames of a video, resulting in a model of 2D structure over time. We discuss techniques to optimize the tracking task and strategies for maximizing accuracy and efficiency. We show visualizations of a variety of motions captured with our pipeline then apply reconstruction techniques to derive 3D structure.

Fractal Fluctuations in Human Walking: Comparison between Auditory and Visually Guided Stepping

Today I read a published paper “Fractal Fluctuations in Human Walking: Comparison between Auditory and Visually Guided Stepping”

The abstract is:

In human locomotion, sensorimotor synchronization of gait consists of the coordination of stepping with rhythmic auditory cues (auditory cueing, AC). AC changes the long-range correlations among consecutive strides (fractal dynamics) into anti-correlations. Visual cueing (VC) is the alignment of step lengths with marks on the floor. The effects of VC on the fluctuation structure of walking have not been investigated. Therefore, the objective was to compare the effects of AC and VC on the fluctuation pattern of basic spatiotemporal gait parameters. Thirty-six healthy individuals walked 3 x 500 strides on an instrumented treadmill with augmented reality capabilities. The conditions were no cueing (NC), AC, and VC. AC included an isochronous metronome. In VC, projected stepping stones were synchronized with the treadmill speed. Detrended fluctuation analysis assessed the correlation structure. The coefficient of variation (CV) was also assessed. The results showed that AC and VC similarly induced a strong anti-correlated pattern in the gait parameters. The CVs were similar between the NC and AC conditions but substantially higher in the VC condition. AC and VC probably mobilize similar motor control pathways and can be used alternatively in gait rehabilitation. However, the increased gait variability induced by VC should be considered.

Today I read a published paper entitled “Fractal Fluctuations in Human Walking: Comparison between Auditory and Visually Guided Stepping”

I have no idea what I am going to do with this knowledge. However, it has given me an idea for two pieces of augmented reality exercise equipment that could be used to motivate people to work out more.

A punching bag with AR projection that designates targets to hit, rapid punches to throw, etc.

An AR treadmill that can project where you should put your foot and coupled with gait analysis, can predict your overall cardio fitness and making estimates of how fast you could run a marathon.

The abstract is:

In human locomotion, sensorimotor synchronization of gait consists of the coordination of stepping with rhythmic auditory cues (auditory cueing, AC). AC changes the long-range correlations among consecutive strides (fractal dynamics) into anti-correlations. Visual cueing (VC) is the alignment of step lengths with marks on the floor. The effects of VC on the fluctuation structure of walking have not been investigated. Therefore, the objective was to compare the effects of AC and VC on the fluctuation pattern of basic spatiotemporal gait parameters. Thirty-six healthy individuals walked 3 x 500 strides on an instrumented treadmill with augmented reality capabilities. The conditions were no cueing (NC), AC, and VC. AC included an isochronous metronome. In VC, projected stepping stones were synchronized with the treadmill speed. Detrended fluctuation analysis assessed the correlation structure. The coefficient of variation (CV) was also assessed. The results showed that AC and VC similarly induced a strong anti-correlated pattern in the gait parameters. The CVs were similar between the NC and AC conditions but substantially higher in the VC condition. AC and VC probably mobilize similar motor control pathways and can be used alternatively in gait rehabilitation. However, the increased gait variability induced by VC should be considered. 

Emotion Detection from Text

Today I read a published paper “Emotion Detection from Text”

The abstract is:

Emotion can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Emotion Detection in text documents is essentially a content – based classification problem involving concepts from the domains of Natural Language Processing as well as Machine Learning. In this paper emotion recognition based on textual data and the techniques used in emotion detection are discussed.

Calculation reduction method for color computer-generated hologram using color space conversion

Today I read a published paper “Calculation reduction method for color computer-generated hologram using color space conversion”

The abstract is:

We report a calculation reduction method for color computer-generated holograms (CGHs) using color space conversion. Color CGHs are generally calculated on RGB space. In this paper, we calculate color CGHs in other color spaces: for example, YCbCr color space. In YCbCr color space, a RGB image is converted to the luminance component (Y), blue-difference chroma (Cb) and red-difference chroma (Cr) components. In terms of the human eye, although the negligible difference of the luminance component is well-recognized, the difference of the other components is not. In this method, the luminance component is normal sampled and the chroma components are down-sampled. The down-sampling allows us to accelerate the calculation of the color CGHs. We compute diffraction calculations from the components, and then we convert the diffracted results in YCbCr color space to RGB color space.

Time manipulation technique for speeding up reinforcement learning in simulations

Today I read a published paper “Time manipulation technique for speeding up reinforcement learning in simulations”

The abstract is:

A technique for speeding up reinforcement learning algorithms by using time manipulation is proposed. It is applicable to failure-avoidance control problems running in a computer simulation. Turning the time of the simulation backwards on failure events is shown to speed up the learning by 260% and improve the state space exploration by 12% on the cart-pole balancing task, compared to the conventional Q-learning and Actor-Critic algorithms.

Procams-Based Cybernetics

Today I read a published paper “Procams-Based Cybernetics”

The abstract is:

Procams-based cybernetics is a unique, emerging research field, which aims at enhancing and supporting our activities by naturally connecting human and computers/machines as a cooperative integrated system via projector-camera systems (procams). It rests on various research domains such as virtual/augmented reality, computer vision, computer graphics, projection display, human computer interface, human robot interaction and so on. This laboratory presentation provides a brief history including recent achievements of our procams-based cybernetics project.

Parking Space Management via Dynamic Performance-Based Pricing

Today I read a published paper “Parking Space Management via Dynamic Performance-Based Pricing”

The abstract is:

In congested urban areas, it remains a pressing challenge to reduce unnecessary vehicle circling for parking while at the same time maximize parking space utilization. In observance of new information technologies that have become readily accessible to drivers and parking agencies, we develop a dynamic non-cooperative bi-level model (i.e. Stackelberg leader-follower game) to set parking prices in real-time for effective parking access and space utilization. The model is expected to fit into an integrated parking pricing and management system, where parking reservations and transactions are facilitated by sensing and informatics infrastructures, that ensures the availability of convenient spaces at equilibrium market prices. It is shown with numerical examples that the proposed dynamic parking pricing model has the potential to virtually eliminate vehicle circling for parking, which results in significant reduction in adverse socioeconomic externalities such as traffic congestion and emissions.

Cross-view Action Modeling, Learning and Recognition

Today I read a published paper “Cross-view Action Modeling, Learning and Recognition”

The abstract is:

Existing methods on video-based action recognition are generally view-dependent, i.e., performing recognition from the same views seen in the training data. We present a novel multiview spatio-temporal AND-OR graph (MST-AOG) representation for cross-view action recognition, i.e., the recognition is performed on the video from an unknown and unseen view. As a compositional model, MST-AOG compactly represents the hierarchical combinatorial structures of cross-view actions by explicitly modeling the geometry, appearance and motion variations. This paper proposes effective methods to learn the structure and parameters of MST-AOG. The inference based on MST-AOG enables action recognition from novel views. The training of MST-AOG takes advantage of the 3D human skeleton data obtained from Kinect cameras to avoid annotating enormous multi-view video frames, which is error-prone and time-consuming, but the recognition does not need 3D information and is based on 2D video input. A new Multiview Action3D dataset has been created and will be released. Extensive experiments have demonstrated that this new action representation significantly improves the accuracy and robustness for cross-view action recognition on 2D videos.

Automated Tracking and Estimation for Control of Non-rigid Cloth

Today I read a published paper “Automated Tracking and Estimation for Control of Non-rigid Cloth”

The abstract is:

This report is a summary of research conducted on cloth tracking for automated textile manufacturing during a two semester long research course at Georgia Tech. This work was completed in 2009. Advances in current sensing technology such as the Microsoft Kinect would now allow me to relax certain assumptions and generally improve the tracking performance. This is because a major part of my approach described in this paper was to track features in a 2D image and use these to estimate the cloth deformation. Innovations such as the Kinect would improve estimation due to the automatic depth information obtained when tracking 2D pixel locations. Additionally, higher resolution camera images would probably give better quality feature tracking. However, although I would use different technology now to implement this tracker, the algorithm described and implemented in this paper is still a viable approach which is why I am publishing this as a tech report for reference. In addition, although the related work is a bit exhaustive, it will be useful to a reader who is new to methods for tracking and estimation as well as modeling of cloth.

Tollan-Xicocotitlan: A reconstructed City by augmented reality

Today I read a published paper “Tollan-Xicocotitlan: A reconstructed City by augmented reality”

The abstract is:

This project presents the analysis, design, implementation and results of Reconstruction Xicocotitlan Tollan-through augmented reality, which will release information about the Toltec culture supplemented by presenting an overview of the main premises of the Xicocotitlan Tollan city supported dimensional models based on the augmented reality technique showing the user a virtual representation of buildings in Tollan.

Convex Relaxations of SE(2) and SE(3) for Visual Pose Estimation

Today I read a published paper “Convex Relaxations of SE(2) and SE(3) for Visual Pose Estimation”

The abstract is:

This paper proposes a new method for rigid body pose estimation based on spectrahedral representations of the tautological orbitopes of $SE(2)$ and $SE(3)$. The approach can use dense point cloud data from stereo vision or an RGB-D sensor (such as the Microsoft Kinect), as well as visual appearance data. The method is a convex relaxation of the classical pose estimation problem, and is based on explicit linear matrix inequality (LMI) representations for the convex hulls of $SE(2)$ and $SE(3)$. Given these representations, the relaxed pose estimation problem can be framed as a robust least squares problem with the optimization variable constrained to these convex sets. Although this formulation is a relaxation of the original problem, numerical experiments indicate that it is indeed exact – i.e. its solution is a member of $SE(2)$ or $SE(3)$ – in many interesting settings. We additionally show that this method is guaranteed to be exact for a large class of pose estimation problems.

Employing fuzzy intervals and loop-based methodology for designing structural signature: an application to symbol recognition

Today I read a published paper “Employing fuzzy intervals and loop-based methodology for designing structural signature: an application to symbol recognition”

The abstract is:

Motivation of our work is to present a new methodology for symbol recognition. We support structural methods for representing visual associations in graphic documents. The proposed method employs a structural approach for symbol representation and a statistical classifier for recognition. We vectorize a graphic symbol, encode its topological and geometrical information by an ARG and compute a signature from this structural graph. To address the sensitivity of structural representations to deformations and degradations, we use data adapted fuzzy intervals while computing structural signature. The joint probability distribution of signatures is encoded by a Bayesian network. This network in fact serves as a mechanism for pruning irrelevant features and choosing a subset of interesting features from structural signatures, for underlying symbol set. Finally we deploy the Bayesian network in supervised learning scenario for recognizing query symbols. We have evaluated the robustness of our method against noise, on synthetically deformed and degraded images of pre-segmented 2D architectural and electronic symbols from GREC databases and have obtained encouraging recognition rates. A second set of experimentation was carried out for evaluating the performance of our method against context noise i.e. symbols cropped from complete documents. The results support the use of our signature by a symbol spotting system.

Personalised product design using virtual interactive techniques

Today I read a published paper “Personalised product design using virtual interactive techniques”

The abstract is:

Use of Virtual Interactive Techniques for personalized product design is described in this paper. Usually products are designed and built by considering general usage patterns and Prototyping is used to mimic the static or working behaviour of an actual product before manufacturing the product. The user does not have any control on the design of the product. Personalized design postpones design to a later stage. It allows for personalized selection of individual components by the user. This is implemented by displaying the individual components over a physical model constructed using Cardboard or Thermocol in the actual size and shape of the original product. The components of the equipment or product such as screen, buttons etc. are then projected using a projector connected to the computer into the physical model. Users can interact with the prototype like the original working equipment and they can select, shape, position the individual components displayed on the interaction panel using simple hand gestures. Computer Vision techniques as well as sound processing techniques are used to detect and recognize the user gestures captured using a web camera and microphone.

Multidimensional Online Robot Motion

Today I read a published paper “Multidimensional Online Robot Motion”

The abstract is:

We consider three related problems of robot movement in arbitrary dimensions: coverage, search, and navigation. For each problem, a spherical robot is asked to accomplish a motion-related task in an unknown environment whose geometry is learned by the robot during navigation. The robot is assumed to have tactile and global positioning sensors. We view these problems from the perspective of (non-linear) competitiveness as defined by Gabriely and Rimon. We first show that in 3 dimensions and higher, there is no upper bound on competitiveness: every online algorithm can do arbitrarily badly compared to the optimal. We then modify the problems by assuming a fixed clearance parameter. We are able to give optimally competitive algorithms under this assumption.