The science papers I've read

Today I read a published paper “Electrotactile vision substitution for 3D trajectory following”

The abstract is:

Navigation for blind persons represents a challenge for researchers in vision substitution. In this field, one of the used techniques to navigate is guidance. In this study, we develop a new approach for 3D trajectory following in which the requested task is to track a light path using computer input devices (keyboard and mouse) or a rigid body handled in front of a stereoscopic camera. The light path is visualized either on direct vision or by way of a electro-stimulation device, the Tongue Display Unit, a 12×12 matrix of electrodes. We improve our method by a series of experiments in which the effect of the modality of perception and that of the input device. Preliminary results indicated a close correlation between the stimulated and recorded trajectories.

Today I read a published paper “Speckle Reduction using Stochastic Distances”

The abstract is:

This paper presents a new approach for filter design based on stochastic distances and tests between distributions. A window is defined around each pixel, samples are compared and only those which pass a goodness-of-fit test are used to compute the filtered value. The technique is applied to intensity Synthetic Aperture Radar (SAR) data, using the Gamma model with varying number of looks allowing, thus, changes in heterogeneity. Modified Nagao-Matsuyama windows are used to define the samples. The proposal is compared with the Lee’s filter which is considered a standard, using a protocol based on simulation. Among the criteria used to quantify the quality of filters, we employ the equivalent number of looks (related to the signal-to-noise ratio), line contrast, and edge preservation. Moreover, we also assessed the filters by the Universal Image Quality Index and the Pearson’s correlation between edges.

Today I read a published paper “Neural Architectures for Robot Intelligence”

The abstract is:

We argue that the direct experimental approaches to elucidate the architecture of higher brains may benefit from insights gained from exploring the possibilities and limits of artificial control architectures for robot systems. We present some of our recent work that has been motivated by that view and that is centered around the study of various aspects of hand actions since these are intimately linked with many higher cognitive abilities. As examples, we report on the development of a modular system for the recognition of continuous hand postures based on neural nets, the use of vision and tactile sensing for guiding prehensile movements of a multifingered hand, and the recognition and use of hand gestures for robot teaching. Regarding the issue of learning, we propose to view real-world learning from the perspective of data mining and to focus more strongly on the imitation of observed actions instead of purely reinforcement-based exploration. As a concrete example of such an effort we report on the status of an ongoing project in our lab in which a robot equipped with an attention system with a neurally inspired architecture is taught actions by using hand gestures in conjunction with speech commands. We point out some of the lessons learnt from this system, and discuss how systems of this kind can contribute to the study of issues at the junction between natural and artificial cognitive systems.

Today I read a published paper titled “Computational Properties of Fiction Writing and Collaborative Work”

The abstract is:

From the earliest days of computing, there have been tools to help shape narrative. Spell-checking, word counts, and readability analysis, give today’s novelists tools that Dickens, Austen, and Shakespeare could only have dreamt of. However, such tools have focused on the word, or phrase levels. In the last decade, research focus has shifted to support for collaborative editing of documents. This work considers more sophisticated attempts to visualise the semantics, pace and rhythm within a narrative through data mining. We describe real life applications in two related domains.

Today I read a published paper “Fast View Frustum Culling of Spatial Object by Analytical Bounding Bin”

The abstract is:

It is a common sense to apply the VFC (view frustum culling) of spatial object to bounding cube of the object in 3D graphics. The accuracy of VFC can not be guaranteed even in cube rotated three-dimensionally. In this paper is proposed a method which is able to carry out more precise and fast VFC of any spatial object in the image domain of cube by an analytic mapping, and is demonstrated the effect of the method for terrain block on global surface.

Today I read a paper titled “A Novel Implementation of QuickHull Algorithm on the GPU”

The abstract is:

We present a novel GPU-accelerated implementation of the QuickHull algorithm for calculating convex hulls of planar point sets.

We also describe a practical solution to demonstrate how to efficiently implement a typical Divide-and-Conquer algorithm on the GPU.

We highly utilize the parallel primitives provided by the library Thrust such as the parallel segmented scan for better efficiency and simplicity.

To evaluate the performance of our implementation, we carry out four groups of experimental tests using two groups of point sets in two modes on the GPU K20c.

Experimental results indicate that: our implementation can achieve the speedups of up to 10.98x over the state-of-art CPU-based convex hull implementation Qhull [16].

In addition, our implementation can find the convex hull of 20M points in about 0.2 seconds.

Today I read a paper titled “Evolutionary Stable Strategies in Games with Fuzzy Payoffs”

The abstract is:

Evolutionarily stable strategy (ESS) is a key concept in evolutionary game theory. ESS provides an evolutionary stability criterion for biological, social and economical behaviors.

In this paper, we develop a new approach to evaluate ESS in symmetric two player games with fuzzy payoffs.

Particularly, every strategy is assigned a fuzzy membership that describes to what degree it is an ESS in presence of uncertainty.

The fuzzy set of ESS characterize the nature of ESS.

The proposed approach avoids loss of any information that happens by the defuzzification method in games and handles uncertainty of payoffs through all steps of finding an ESS.

We use the satisfaction function to compare fuzzy payoffs, and adopts the fuzzy decision rule to obtain the membership function of the fuzzy set of ESS.

The theorem shows the relation between fuzzy ESS and fuzzy Nash quilibrium.

The numerical results illustrate the proposed method is an appropriate generalization of ESS to fuzzy payoff games.

Today I read a paper titled “Indoor 3D Video Monitoring Using Multiple Kinect Depth-Cameras”

The abstract is:

This article describes the design and development of a system for remote indoor 3D monitoring using an undetermined number of Microsoft(R) Kinect sensors.

In the proposed client-server system, the Kinect cameras can be connected to different computers, addressing this way the hardware limitation of one sensor per USB controller.

The reason behind this limitation is the high bandwidth needed by the sensor, which becomes also an issue for the distributed system TCP/IP communications.

Since traffic volume is too high, 3D data has to be compressed before it can be sent over the network.

The solution consists in selfcoding the Kinect data into RGB images and then using a standard multimedia codec to compress color maps.

Information from different sources is collected into a central client computer, where point clouds are transformed to reconstruct the scene in 3D.

An algorithm is proposed to merge the skeletons detected locally by each Kinect conveniently, so that monitoring of people is robust to self and inter-user occlusions.

Final skeletons are labeled and trajectories of every joint can be saved for event reconstruction or further analysis.

Today I read a paper titled “An end-to-end machine learning system for harmonic analysis of music”

The abstract is:

We present a new system for simultaneous estimation of keys, chords, and bass notes from music audio.

It makes use of a novel chromagram representation of audio that takes perception of loudness into account.

Furthermore, it is fully based on machine learning (instead of expert knowledge), such that it is potentially applicable to a wider range of genres as long as training data is available.

As compared to other models, the proposed system is fast and memory efficient, while achieving state-of-the-art performance.

Today I read a paper titled “Modeling the Rise in Internet-based Petitions”

The abstract is:

Contemporary collective action, much of which involves social media and other Internet-based platforms, leaves a digital imprint which may be harvested to better understand the dynamics of mobilization.

Petition signing is an example of collective action which has gained in popularity with rising use of social media and provides such data for the whole population of petition signatories for a given platform. This paper tracks the growth curves of all 20,000 petitions to the UK government over 18 months, analyzing the rate of growth and outreach mechanism.

Previous research has suggested the importance of the first day to the ultimate success of a petition, but has not examined early growth within that day, made possible here through hourly resolution in the data.

The analysis shows that the vast majority of petitions do not achieve any measure of success; over 99 percent fail to get the 10,000 signatures required for an official response and only 0.1 percent attain the 100,000 required for a parliamentary debate.

We analyze the data through a multiplicative process model framework to explain the heterogeneous growth of signatures at the population level.

We define and measure an average outreach factor for petitions and show that it decays very fast (reducing to 0.1% after 10 hours).

After 24 hours, a petition’s fate is virtually set.

The findings seem to challenge conventional analyses of collective action from economics and political science, where the production function has been assumed to follow an S-shaped curve.

Today I read a paper titled “Dynamic Facial Expression of Emotion Made Easy”

The abstract is:

Facial emotion expression for virtual characters is used in a wide variety of areas.

Often, the primary reason to use emotion expression is not to study emotion expression generation per se, but to use emotion expression in an application or research project.

What is then needed is an easy to use and flexible, but also validated mechanism to do so.

In this report we present such a mechanism.

It enables developers to build virtual characters with dynamic affective facial expressions.

The mechanism is based on Facial Action Coding.

It is easy to implement, and code is available for download.

To show the validity of the expressions generated with the mechanism we tested the recognition accuracy for 6 basic emotions (joy, anger, sadness, surprise, disgust, fear) and 4 blend emotions (enthusiastic, furious, frustrated, and evil).

Additionally we investigated the effect of VC distance (z-coordinate), the effect of the VC’s face morphology (male vs. female), the effect of a lateral versus a frontal presentation of the expression, and the effect of intensity of the expression.

Participants (n=19, Western and Asian subjects) rated the intensity of each expression for each condition (within subject setup) in a non forced choice manner.

All of the basic emotions were uniquely perceived as such.

Further, the blends and confusion details of basic emotions are compatible with findings in psychology.

Today I read a paper titled “Mobile augmented reality survey: a bottom-up approach”

The abstract is:

Augmented Reality (AR) is becoming mobile.

Mobile devices have many constraints but also rich new features that traditional desktop computers do not have.

There are several survey papers on AR, but none is dedicated to Mobile Augmented Reality (MAR).

Our work serves the purpose of closing this gap.

The contents are organized with a bottom-up approach.

We first present the state-of-the-art in system components including hardware platforms, software frameworks and display devices, follows with enabling technologies such as tracking and data management.

We then survey the latest technologies and methods to improve run-time performance and energy efficiency for practical implementation.

On top of these, we further introduce the application fields and several typical MAR applications.

Finally we conclude the survey with several challenge problems, which are under exploration and require great research efforts in the future.

Today I read a paper titled “Learning discriminative trajectorylet detector sets for accurate skeleton-based action recognition”

The abstract is:

The introduction of low-cost RGB-D sensors has promoted the research in skeleton-based human action recognition.

Devising a representation suitable for characterising actions on the basis of noisy skeleton sequences remains a challenge, however.

We here provide two insights into this challenge.

First, we show that the discriminative information of a skeleton sequence usually resides in a short temporal interval and we propose a simple-but-effective local descriptor called trajectorylet to capture the static and kinematic information within this interval.

Second, we further propose to encode each trajectorylet with a discriminative trajectorylet detector set which is selected from a large number of candidate detectors trained through exemplar-SVMs.

The action-level representation is obtained by pooling trajectorylet encodings.

Evaluating on standard datasets acquired from the Kinect sensor, it is demonstrated that our method obtains superior results over existing approaches under various experimental setups.

Today I read a paper titled “Algorithms to automatically quantify the geometric similarity of anatomical surfaces”

The abstract is:

We describe new approaches for distances between pairs of 2-dimensional surfaces (embedded in 3-dimensional space) that use local structures and global information contained in inter-structure geometric relationships.

We present algorithms to automatically determine these distances as well as geometric correspondences.

This is motivated by the aspiration of students of natural science to understand the continuity of form that unites the diversity of life.

At present, scientists using physical traits to study evolutionary relationships among living and extinct animals analyze data extracted from carefully defined anatomical correspondence points (landmarks).

Identifying and recording these landmarks is time consuming and can be done accurately only by trained morphologists.

This renders these studies inaccessible to non-morphologists, and causes phenomics to lag behind genomics in elucidating evolutionary patterns.

Unlike other algorithms presented for morphological correspondences our approach does not require any preliminary marking of special features or landmarks by the user.

It also differs from other seminal work in computational geometry in that our algorithms are polynomial in nature and thus faster, making pairwise comparisons feasible for significantly larger numbers of digitized surfaces.

We illustrate our approach using three datasets representing teeth and different bones of primates and humans, and show that it leads to highly accurate results.

Today I read a paper titled “Face Prediction Model for an Automatic Age-invariant Face Recognition System”

The abstract is:

Automated face recognition and identification softwares are becoming part of our daily life; it finds its abode not only with Facebook’s auto photo tagging, Apple’s iPhoto, Google’s Picasa, Microsoft’s Kinect, but also in Homeland Security Department’s dedicated biometric face detection systems.

Most of these automatic face identification systems fail where the effects of aging come into the picture.

Little work exists in the literature on the subject of face prediction that accounts for aging, which is a vital part of the computer face recognition systems.

In recent years, individual face components’ (e.g. eyes, nose, mouth) features based matching algorithms have emerged, but these approaches are still not efficient.

Therefore, in this work we describe a Face Prediction Model (FPM), which predicts human face aging or growth related image variation using Principle Component Analysis (PCA) and Artificial Neural Network (ANN) learning techniques.

The FPM captures the facial changes, which occur with human aging and predicts the facial image with a few years of gap with an acceptable accuracy of face matching from 76 to 86%.

Today I read a paper titled “Robust and Real Time Detection of Curvy Lanes (Curves) with Desired Slopes for Driving Assistance and Autonomous Vehicles”

The abstract is:

One of the biggest reasons for road accidents is curvy lanes and blind turns.

Even one of the biggest hurdles for new autonomous vehicles is to detect curvy lanes, multiple lanes and lanes with a lot of discontinuity and noise.

This paper presents very efficient and advanced algorithm for detecting curves having desired slopes (especially for detecting curvy lanes in real time) and detection of curves (lanes) with a lot of noise, discontinuity and disturbances.

Overall aim is to develop robust method for this task which is applicable even in adverse conditions.

Even in some of most famous and useful libraries like OpenCV and Matlab, there is no function available for detecting curves having desired slopes , shapes, discontinuities.

Only few predefined shapes like circle, ellipse, etc, can be detected using presently available functions.

Proposed algorithm can not only detect curves with discontinuity, noise, desired slope but also it can perform shadow and illumination correction and detect/ differentiate between different curves.

Today I read a paper titled “Estimating 3D Human Shapes from Measurements”

The abstract is:

The recent advances in 3-D imaging technologies give rise to databases of human shapes, from which statistical shape models can be built.

These statistical models represent prior knowledge of the human shape and enable us to solve shape reconstruction problems from partial information.

Generating human shape from traditional anthropometric measurements is such a problem, since these 1-D measurements encode 3-D shape information.

Combined with a statistical shape model, these easy-to-obtain measurements can be leveraged to create 3D human shapes.

However, existing methods limit the creation of the shapes to the space spanned by the database and thus require a large amount of training data.

In this paper, we introduce a technique that extrapolates the statistically inferred shape to fit the measurement data using nonlinear optimization.

This method ensures that the generated shape is both human-like and satisfies the measurement conditions.

We demonstrate the effectiveness of the method and compare it to existing approaches through extensive experiments, using both synthetic data and real human measurements.

Today I read a paper titled “Virtual Texturing”

The abstract is:

In this thesis a rendering system and an accompanying tool chain for Virtual Texturing is presented.

Our tools allow to automatically retexture existing geometry in order to apply unique texturing on each face.

Furthermore we investigate several techniques that try to minimize visual artifacts in the case that only a small amount of pages can be streamed per frame.

We analyze the influence of different heuristics that are responsible for the page selection.

Alongside these results we present a measurement method to allow the comparison of our heuristics.

Today I read a paper titled “A Behavior-based Approach for Multi-agent Q-learning for Autonomous Exploration”

The abstract is:

The use of mobile robots is being popular over the world mainly for autonomous explorations in hazardous/ toxic or unknown environments.

This exploration will be more effective and efficient if the explorations in unknown environment can be aided with the learning from past experiences.

Currently reinforcement learning is getting more acceptances for implementing learning in robots from the system-environment interactions.

This learning can be implemented using the concept of both single-agent and multiagent.

This paper describes such a multiagent approach for implementing a type of reinforcement learning using a priority based behaviour-based architecture.

This proposed methodology has been successfully tested in both indoor and outdoor environments.

Today I read a paper titled “Attraction-Based Receding Horizon Path Planning with Temporal Logic Constraints”

The abstract is:

Our goal in this paper is to plan the motion of a robot in a partitioned environment with dynamically changing, locally sensed rewards.

We assume that arbitrary assumptions on the reward dynamics can be given.

The robot aims to accomplish a high-level temporal logic surveillance mission and to locally optimize the collection of the rewards in the visited regions.

These two objectives often conflict and only a compromise between them can be reached.

We address this issue by taking into consideration a user-defined preference function that captures the trade-off between the importance of collecting high rewards and the importance of making progress towards a surveyed region.

Our solution leverages ideas from the automata-based approach to model checking.

We demonstrate the utilization and benefits of the suggested framework in an illustrative example.

Today I read a paper titled “Algorithms for two variants of Satisfaction Approval Voting”

The abstract is:

Multi-winner voting rules based on approval ballots have received increased attention in recent years.

In particular Satisfaction Approval Voting (SAV) and its variants have been proposed.

In this note, we show that the winning set can be determined in polynomial time for two prominent and natural variants of SAV.

We thank Arkadii Slinko for suggesting these problems in a talk at the Workshop on Challenges in Algorithmic Social Choice, Bad Belzig, October 11, 2014.

Today I read a paper titled “Immersive and Collaborative Data Visualization Using Virtual Reality Platforms”

The abstract is:

Effective data visualization is a key part of the discovery process in the era of big data.

It is the bridge between the quantitative content of the data and human intuition, and thus an essential component of the scientific path from data into knowledge and understanding.

Visualization is also essential in the data mining process, directing the choice of the applicable algorithms, and in helping to identify and remove bad data from the analysis.

However, a high complexity or a high dimensionality of modern data sets represents a critical obstacle.

How do we visualize interesting structures and patterns that may exist in hyper-dimensional data spaces? A better understanding of how we can perceive and interact with multi dimensional information poses some deep questions in the field of cognition technology and human computer interaction.

To this effect, we are exploring the use of immersive virtual reality platforms for scientific data visualization, both as software and inexpensive commodity hardware.

These potentially powerful and innovative tools for multi dimensional data visualization can also provide an easy and natural path to a collaborative data visualization and exploration, where scientists can interact with their data and their colleagues in the same visual space.

Immersion provides benefits beyond the traditional desktop visualization tools: it leads to a demonstrably better perception of a datascape geometry, more intuitive data understanding, and a better retention of the perceived relationships in the data.

Today I read a paper titled “A Self-Supervised Terrain Roughness Estimator for Off-Road Autonomous Driving”

The abstract is:

We present a machine learning approach for estimating the second derivative of a drivable surface, its roughness.

Robot perception generally focuses on the first derivative, obstacle detection.

However, the second derivative is also important due to its direct relation (with speed) to the shock the vehicle experiences.

Knowing the second derivative allows a vehicle to slow down in advance of rough terrain.

Estimating the second derivative is challenging due to uncertainty.

For example, at range, laser readings may be so sparse that significant information about the surface is missing.

Also, a high degree of precision is required in projecting laser readings.

This precision may be unavailable due to latency or error in the pose estimation. We model these sources of error as a multivariate polynomial.

Its coefficients are learned using the shock data as ground truth — the accelerometers are used to train the lasers.

The resulting classifier operates on individual laser readings from a road surface described by a 3D point cloud.

The classifier identifies sections of road where the second derivative is likely to be large.

Thus, the vehicle can slow down in advance, reducing the shock it experiences.

The algorithm is an evolution of one we used in the 2005 DARPA Grand Challenge.

We analyze it using data from that route.

Today I read a paper titled “Equitable Partitioning Policies for Mobile Robotic Networks”

How can you not like a paper that exploits the usefulness of the classic Lloyd algorithm.

The abstract is:

The most widely applied strategy for workload sharing is to equalize the workload assigned to each resource.

In mobile multi-agent systems, this principle directly leads to equitable partitioning policies in which (i) the workspace is divided into subregions of equal measure, (ii) there is a bijective correspondence between agents and subregions, and (iii) each agent is responsible for service requests originating within its own subregion.

In this paper, we design provably correct, spatially-distributed and adaptive policies that allow a team of agents to achieve a convex and equitable partition of a convex workspace, where each subregion has the same measure.

We also consider the issue of achieving convex and equitable partitions where subregions have shapes similar to those of regular polygons.

Our approach is related to the classic Lloyd algorithm, and exploits the unique features of power diagrams.

We discuss possible applications to routing of vehicles in stochastic and dynamic environments.

Simulation results are presented and discussed.

Today I read a paper titled “Various Types of Aesthetic Curves”

The abstract is:

The research on developing planar curves to produce visually pleasing products (ranges from electric appliances to car body design) and indentifying/modifying planar curves for special purposes namely for railway design, highway design and robot trajectories have been progressing since 1970s.

The pattern of research in this field of study has branched to five major groups namely curve synthesis, fairing process, improvement in control of natural spiral, construction of new type of planar curves and, natural spiral fitting & approximation techniques.

The purpose of is this paper is to briefly review recent progresses in Computer Aided Geometric Design (CAGD) focusing on the topics states above.

Today I read a paper titled “Vibrotactile Stimulus Frequency Optimization for the Haptic BCI Prototype”

The abstract is:

The paper presents results from a psychophysical study conducted to optimize vibrotactile stimuli delivered to subject finger tips in order to evoke the somatosensory responses to be utilized next in a haptic brain computer interface (hBCI) paradigm.

We also present the preliminary EEG evoked responses for the chosen stimulating frequency.

The obtained results confirm our hypothesis that the hBCI paradigm concept is valid and it will allow for rapid stimuli presentation in order to improve information-transfer-rate (ITR) of the BCI.

Today I read a paper titled “On the Covariance of ICP-based Scan-matching Techniques”

The abstract is:

This paper considers the problem of estimating the covariance of roto-translations computed by the Iterative Closest Point (ICP) algorithm.

The problem is relevant for localization of mobile robots and vehicles equipped with depth-sensing cameras (e.g., Kinect) or Lidar (e.g., Velodyne).

The closed-form formulas for covariance proposed in previous literature generally build upon the fact that the solution to ICP is obtained by minimizing a linear least-squares problem.

In this paper, we show this approach needs caution because the rematching step of the algorithm is not explicitly accounted for, and applying it to the point-to-point version of ICP leads to completely erroneous covariances.

We then provide a formal mathematical proof why the approach is valid in the point-to-plane version of ICP, which validates the intuition and experimental results of practitioners.

Today I read a paper titled “On the Dynamics of Human Proximity for Data Diffusion in Ad-Hoc Networks”

The abstract is:

We report on a data-driven investigation aimed at understanding the dynamics of message spreading in a real-world dynamical network of human proximity.

We use data collected by means of a proximity-sensing network of wearable sensors that we deployed at three different social gatherings, simultaneously involving several hundred individuals.

We simulate a message spreading process over the recorded proximity network, focusing on both the topological and the temporal properties.

We show that by using an appropriate technique to deal with the temporal heterogeneity of proximity events, a universal statistical pattern emerges for the delivery times of messages, robust across all the data sets.

Our results are useful to set constraints for generic processes of data dissemination, as well as to validate established models of human mobility and proximity that are frequently used to simulate realistic behaviors.

Today I read a paper titled “Anatomical Feature-guided Volumetric Registration of Multimodal Prostate MRI”

The abstract is:

Radiological imaging of prostate is becoming more popular among researchers and clinicians in searching for diseases, primarily cancer.

Scans might be acquired at different times, with patient movement between scans, or with different equipment, resulting in multiple datasets that need to be registered.

For this issue, we introduce a registration method using anatomical feature-guided mutual information.

Prostate scans of the same patient taken in three different orientations are first aligned for the accurate detection of anatomical features in 3D.

Then, our pipeline allows for multiple modalities registration through the use of anatomical features, such as the interior urethra of prostate and gland utricle, in a bijective way.

The novelty of this approach is the application of anatomical features as the pre-specified corresponding landmarks for prostate registration.

We evaluate the registration results through both artificial and clinical datasets

Registration accuracy is evaluated by performing statistical analysis of local intensity differences or spatial differences of anatomical landmarks between various MR datasets.

Evaluation results demonstrate that our method statistics-significantly improves the quality of registration.

Although this strategy is tested for MRI-guided brachytherapy, the preliminary results from these experiments suggest that it can be also applied to other settings such as transrectal ultrasound-guided or CT-guided therapy, where the integration of preoperative MRI may have a significant impact upon treatment planning and guidance.

Today I read a paper titled “Adaptive Locomotion of Multibody Snake-like Robot”

The abstract is:

This paper represents an adaptive rhythmic control for a snake-like robot with 25 degrees of freedom.

The adaptive gait control is implemented in algorithmic way in simulation and on a real robot.

We investigated behavioral and energetic properties of this control and a dynamics of different body segments.

It turned out that despite using homogeneous generators, physical constraints have an inhomogeneous impact on neighbor body segments.

By analytical modeling of such dynamics, it may result in heterogeneous coupling of oscillators for a rhythmic control and impact scalability and synchronization effects of gait pattern generators.

Today I read a paper titled “Automation of Mobile Pick and Place Robotic System for Small Food Industry”

The abstract is:

The use of robotics in food industry is becoming more popular in recent years.

The trend seems to continue as long as the robotics technology meets diverse and challenging needs of the food producers.

Rapid developments in digital computers and control systems technologies have significant impact in robotics like any other engineering fields.

By utilizing new hardware and software tools, design of these complex systems that need strong integration of distinct disciplines is no longer difficult compared to the past.

Therefore, the purpose of this paper is to design and implement a micro-controller based on reliable and high performance robotic system for food / biscuit manufacturing line.

We propose a design of a vehicle.

The robot is capable of picking unbaked biscuits tray and places them into furnace and then after baking it picks the biscuits tray from the furnace.

A special gripper is designed to pick and place the biscuits tray with flexibility.

Today I read a paper titled “Dynamical issues in interactive representation of physical objects”

The abstract is:

The quality of a simulator equipped with a haptic interface is given by the dynamical properties of its components: haptic interface, simulator and control system.

Some application areas of such kind of simulator like musical synthesis, animation or more general, instrumental art have specific requirements as for the “haptic rendering” of small movements that go beyond the usual haptic interfaces allow.

Object properties variability and different situations of object combination represent important aspects of such type of application which makes that the user can be interested as much in the restitution of certain global properties of an entire object domain as in the restitution of properties that are specific to an isolate object.

In the traditional approaches, the usual criteria are founded on the paradigm of transparency and are related to the impedance error introduced by the technical aspects of the system.

As a general aim, rather than to minimize these effects, we look to characterize them by physical metaphors conferring to haptic medium the role of a tool.

This positioning leads to firstly analyze the natural human object interaction as a simplified evolutive system and then considers its synthesis in the case of the interactive physical simulation.

By means of a frequential method, this approach is presented for some elementary configurations of the simulator

Today I read a paper titled “Light-field Microscopy with a Consumer Light-field Camera”

The abstract is:

We explore the use of inexpensive consumer light- field camera technology for the purpose of light-field mi- croscopy.

Our experiments are based on the Lytro (first gen- eration) camera.

Unfortunately, the optical systems of the Lytro and those of microscopes are not compatible, lead- ing to a loss of light-field information due to angular and spatial vignetting when directly recording microscopic pic- tures.

We therefore consider an adaptation of the Lytro op- tical system.

We demonstrate that using the Lytro directly as an oc- ular replacement, leads to unacceptable spatial vignetting.

However, we also found a setting that allows the use of the Lytro camera in a virtual imaging mode which prevents the information loss to a large extent.

We analyze the new vir- tual imaging mode and use it in two different setups for im- plementing light-field microscopy using a Lytro camera.

As a practical result, we show that the camera can be used for low magnification work, as e.g. common in quality control, surface characterization, etc.

Today I read a paper titled “Speech animation using electromagnetic articulography as motion capture data”

The abstract is:

Electromagnetic articulography (EMA) captures the position and orientation of a number of markers, attached to the articulators, during speech.

As such, it performs the same function for speech that conventional motion capture does for full-body movements acquired with optical modalities, a long-time staple technique of the animation industry.

In this paper, EMA data is processed from a motion-capture perspective and applied to the visualization of an existing multimodal corpus of articulatory data, creating a kinematic 3D model of the tongue and teeth by adapting a conventional motion capture based animation paradigm.

This is accomplished using off-the-shelf, open-source software.

Such an animated model can then be easily integrated into multimedia applications as a digital asset, allowing the analysis of speech production in an intuitive and accessible manner.

The processing of the EMA data, its co-registration with 3D data from vocal tract magnetic resonance imaging (MRI) and dental scans, and the modeling workflow are presented in detail, and several issues discussed.

Today I read a paper titled “Self-organized adaptation of a simple neural circuit enables complex robot behaviour”

The abstract is:

Controlling sensori-motor systems in higher animals or complex robots is a challenging combinatorial problem, because many sensory signals need to be simultaneously coordinated into a broad behavioural spectrum.

To rapidly interact with the environment, this control needs to be fast and adaptive.

Current robotic solutions operate with limited autonomy and are mostly restricted to few behavioural patterns.

Here we introduce chaos control as a new strategy to generate complex behaviour of an autonomous robot.

In the presented system, 18 sensors drive 18 motors via a simple neural control circuit, thereby generating 11 basic behavioural patterns (e.g., orienting, taxis, self-protection, various gaits) and their combinations.

The control signal quickly and reversibly adapts to new situations and additionally enables learning and synaptic long-term storage of behaviourally useful motor responses.

Thus, such neural control provides a powerful yet simple way to self-organize versatile behaviours in autonomous agents with many degrees of freedom.

Today I read a paper titled “A level-set-based method for fixing overhangs in 3D printing”

The abstract is:
3D printers based on the Fused Decomposition Modeling create objects layer-by-layer dropping fused material

As a consequence, strong overhangs cannot be printed because the new-come material does not find a suitable support over the last deposed layer

In these cases, one can add some support structures (scaffolds) which make the object printable, to be removed at the end

In this paper we propose a level-set method to create object-dependent support structures, specifically conceived to reduce both the amount of additional material and the printing time

We also review some open problems about 3D printing which can be of interests for the mathematical community

Today I read a paper titled “Unit Vector Games”

The abstract is:
McLennan and Tourky (2010) showed that “imitation games” provide a new view of the computation of Nash equilibria of bimatrix games with the Lemke-Howson algorithm

In an imitation game, the payoff matrix of one of the players is the identity matrix

We study the more general “unit vector games”, which are already known, where the payoff matrix of one player is composed of unit vectors

Our main application is a simplification of the construction by Savani and von Stengel (2006) of bimatrix games where two basic equilibrium-finding algorithms take exponentially many steps: the Lemke-Howson algorithm, and support enumeration.

Today I read a paper titled “Single-Pass GPU-Raycasting for Structured Adaptive Mesh Refinement Data”

The abstract is:
Structured Adaptive Mesh Refinement (SAMR) is a popular numerical technique to study processes with high spatial and temporal dynamic range

It reduces computational requirements by adapting the lattice on which the underlying differential equations are solved to most efficiently represent the solution

Particularly in astrophysics and cosmology such simulations now can capture spatial scales ten orders of magnitude apart and more

The irregular locations and extensions of the refined regions in the SAMR scheme and the fact that different resolution levels partially overlap, poses a challenge for GPU-based direct volume rendering methods

kD-trees have proven to be advantageous to subdivide the data domain into non-overlapping blocks of equally sized cells, optimal for the texture units of current graphics hardware, but previous GPU-supported raycasting approaches for SAMR data using this data structure required a separate rendering pass for each node, preventing the application of many advanced lighting schemes that require simultaneous access to more than one block of cells

In this paper we present a single-pass GPU-raycasting algorithm for SAMR data that is based on a kD-tree

The tree is efficiently encoded by a set of 3D-textures, which allows to adaptively sample complete rays entirely on the GPU without any CPU interaction

We discuss two different data storage strategies to access the grid data on the GPU and apply them to several datasets to prove the benefits of the proposed method

Today I read a paper titled “3D Hand Pose Detection in Egocentric RGB-D Images”

The abstract is:
We focus on the task of everyday hand pose estimation from egocentric viewpoints

For this task, we show that depth sensors are particularly informative for extracting near-field interactions of the camera wearer with his/her environment

Despite the recent advances in full-body pose estimation using Kinect-like sensors, reliable monocular hand pose estimation in RGB-D images is still an unsolved problem

The problem is considerably exacerbated when analyzing hands performing daily activities from a first-person viewpoint, due to severe occlusions arising from object manipulations and a limited field-of-view

Our system addresses these difficulties by exploiting strong priors over viewpoint and pose in a discriminative tracking-by-detection framework

Our priors are operationalized through a photorealistic synthetic model of egocentric scenes, which is used to generate training data for learning depth-based pose classifiers

We evaluate our approach on an annotated dataset of real egocentric object manipulation scenes and compare to both commercial and academic approaches

Our method provides state-of-the-art performance for both hand detection and pose estimation in egocentric RGB-D images

Today I read a paper titled “Computer- and robot-assisted Medical Intervention”

The abstract is:
Medical robotics includes assistive devices used by the physician in order to make his/her diagnostic or therapeutic practices easier and more efficient

This chapter focuses on such systems

It introduces the general field of Computer-Assisted Medical Interventions, its aims, its different components and describes the place of robots in that context

The evolutions in terms of general design and control paradigms in the development of medical robots are presented and issues specific to that application domain are discussed

A view of existing systems, on-going developments and future trends is given

A case-study is detailed

Other types of robotic help in the medical environment (such as for assisting a handicapped person, for rehabilitation of a patient or for replacement of some damaged/suppressed limbs or organs) are out of the scope of this chapter

Today I read a paper titled “A novel approach for determining fatigue resistances of different muscle groups in static cases”

The abstract is:
In ergonomics and biomechanics, muscle fatigue models based on maximum endurance time (MET) models are often used to integrate fatigue effect into ergonomic and biomechanical application

However, due to the empirical principle of those MET models, the disadvantages of this method are: 1) the MET models cannot reveal the muscle physiology background very well; 2) there is no general formation for those MET models to predict MET

In this paper, a theoretical MET model is extended from a simple muscle fatigue model with consideration of the external load and maximum voluntary contraction in passive static exertion cases

The universal availability of the extended MET model is analyzed in comparison to 24 existing empirical MET models

Using mathematical regression method, 21 of the 24 MET models have intraclass correlations over 0.9, which means the extended MET model could replace the existing MET models in a general and computationally efficient way

In addition, an important parameter, fatigability (or fatigue resistance) of different muscle groups, could be calculated via the mathematical regression approach

Its mean value and its standard deviation are useful for predicting MET values of a given population during static operations

The possible reasons influencing the fatigue resistance were classified and discussed, and it is still a very challenging work to find out the quantitative relationship between the fatigue resistance and the influencing factors

Today I read a paper titled “3-Phase Recognition Approach to Pseudo 3D Building Generation from 2D Floor Plan”

The abstract is:
Nowadays three dimension (3D) architectural visualisation has become a powerful tool in the conceptualisation, design and presentation of architectural products in the construction industry, providing realistic interaction and walkthrough on engineering products

Traditional ways of implementing 3D models involves the use of specialised 3D authoring tools along with skilled 3D designers with blueprints of the model and this is a slow and laborious process

The aim of this paper is to automate this process by simply analyzing the blueprint document and generating the 3D scene automatically

For this purpose we have devised a 3-Phase recognition approach to pseudo 3D building generation from 2D floor plan and developed a software accordingly

Our 3-phased 3D building system has been implemented using C, C++ and OpenCV library [24] for the Image Processing module; The Save Module generated an XML file for storing the processed floor plan objects attributes; while the Irrlitch [14] game engine was used to implement the Interactive 3D module

Though still at its infancy, our proposed system gave commendable results

We tested our system on 6 floor plans with complexities ranging from low to high and the results seems to be very promising with an average processing time of around 3s and a 3D generation in 4s

In addition the system provides an interactive walk-though and allows users to modify components

Today I read a paper titled “Animation of 3D Human Model Using Markerless Motion Capture Applied To Sports”

The abstract is:
Markerless motion capture is an active research in 3D virtualization

In proposed work we presented a system for markerless motion capture for 3D human character animation, paper presents a survey on motion and skeleton tracking techniques which are developed or are under development

The paper proposed a method to transform the motion of a performer to a 3D human character (model), the 3D human character performs similar movements as that of a performer in real time

In the proposed work, human model data will be captured by Kinect camera, processed data will be applied on 3D human model for animation

3D human model is created using open source software (MakeHuman)

Anticipated dataset for sport activity is considered as input which can be applied to any HCI application

Today I read a paper titled “Implementation of Hand Detection based Techniques for Human Computer Interaction”

The abstract is:
The computer industry is developing at a fast pace

With this development almost all of the fields under computers have advanced in the past couple of decades

But the same technology is being used for human computer interaction that was used in 1970s

Even today the same type of keyboard and mouse is used for interacting with computer systems

With the recent boom in the mobile segment touchscreens have become popular for interaction with cell phones

But these touchscreens are rarely used on traditional systems

This paper tries to introduce methods for human computer interaction using the users hand which can be used both on traditional computer platforms as well as cell phones

The methods explain how the users detected hand can be used as input for applications and also explain applications that can take advantage of this type of interaction mechanism

Today I read a paper titled “A Unified Framework for Multi-Sensor HDR Video Reconstruction”

The abstract is:
One of the most successful approaches to modern high quality HDR-video capture is to use camera setups with multiple sensors imaging the scene through a common optical system

However, such systems pose several challenges for HDR reconstruction algorithms

Previous reconstruction techniques have considered debayering, denoising, resampling (align- ment) and exposure fusion as separate problems

In contrast, in this paper we present a unifying approach, performing HDR assembly directly from raw sensor data

Our framework includes a camera noise model adapted to HDR video and an algorithm for spatially adaptive HDR reconstruction based on fitting of local polynomial approximations to observed sensor data

The method is easy to implement and allows reconstruction to an arbitrary resolution and output mapping

We present an implementation in CUDA and show real-time performance for an experimental 4 Mpixel multi-sensor HDR video system

We further show that our algorithm has clear advantages over existing methods, both in terms of flexibility and reconstruction quality

Today I read a paper titled “Social Data Mining through Distributed Mobile Sensing”

The abstract is:
In this article, we present a distributed framework for collecting and analyzing environmental and location data recorded by human users (carriers) with the use of portable sensors

We demonstrate the data mining analysis potential among the recorded environmental and location variables, as well as the potential for classification analysis of human activities

We recognize that the success of such an experimental framework relies on the adoption rate by its candidate user network; thus, we have built our experimental prototype on top of hardware equipment already embedded within the potential users’ everyday routine – i.e. hardware sensors installed on modern mobile phones

Finally, we present preliminary analysis results on our collected data sample, as well as potential further work directions and proposed use case scenarios

Today I read a paper titled “Reversible Circuit Optimization via Leaving the Boolean Domain”

The abstract is:
For years, the quantum/reversible circuit community has been convinced that: a) the addition of auxiliary qubits is instrumental in constructing a smaller quantum circuit; and, b) the introduction of quantum gates inside reversible circuits may result in more efficient designs

This paper presents a systematic approach to optimizing reversible (and quantum) circuits via the introduction of auxiliary qubits and quantum gates inside circuit designs

This advances our understanding of what may be achieved with a) and b)

Today I read a paper titled “Finding Convex Hulls Using Quickhull on the GPU”

The abstract is:
We present a convex hull algorithm that is accelerated on commodity graphics hardware

We analyze and identify the hurdles of writing a recursive divide and conquer algorithm on the GPU and divise a framework for representing this class of problems

Our framework transforms the recursive splitting step into a permutation step that is well-suited for graphics hardware

Our convex hull algorithm of choice is Quickhull

Our parallel Quickhull implementation (for both 2D and 3D cases) achieves an order of magnitude speedup over standard computational geometry libraries

Today I read a paper titled “Reinforcement Learning and Nonparametric Detection of Game-Theoretic Equilibrium Play in Social Networks”

The abstract is:
This paper studies two important signal processing aspects of equilibrium behavior in non-cooperative games arising in social networks, namely, reinforcement learning and detection of equilibrium play

The first part of the paper presents a reinforcement learning (adaptive filtering) algorithm that facilitates learning an equilibrium by resorting to diffusion cooperation strategies in a social network

Agents form homophilic social groups, within which they exchange past experiences over an undirected graph

It is shown that, if all agents follow the proposed algorithm, their global behavior is attracted to the correlated equilibria set of the game

The second part of the paper provides a test to detect if the actions of agents are consistent with play from the equilibrium of a concave potential game

The theory of revealed preference from microeconomics is used to construct a non-parametric decision test and statistical test which only require the probe and associated actions of agents

A stochastic gradient algorithm is given to optimize the probe in real time to minimize the Type-II error probabilities of the detection test subject to specified Type-I error probability

We provide a real-world example using the energy market, and a numerical example to detect malicious agents in an online social network.

Today I read a paper titled “An Approximation Algorithm for Computing Shortest Paths in Weighted 3-d Domains”

The abstract is:
We present the first polynomial time approximation algorithm for computing shortest paths in weighted three-dimensional domains

The efficiency of the proposed algorithm is based on an in-depth study of the local behavior of geodesic paths and additive Voronoi diagrams in weighted three-dimensional domains, which are of independent interest

The paper extends the results of Aleksandrov, Maheshwari and Sack [JACM 2005] to three dimensions