Today I read a paper titled “Hand Segmentation for Hand-Object Interaction from Depth map”
The abstract is:
Hand-object interaction is important for many applications such as augmented reality, medical application, and human-robot interaction.
Hand segmentation is a necessary pre-process to estimate hand pose and to recognize hand gesture or object in interaction.
However, current hand segmentation method for hand-object interaction is based on color information which is not robust to objects with skin color, skin pigment difference, and light condition variations.
Therefore, we propose the first hand segmentation method for hand-object interaction using depth map.
This is challenging because of only small depth difference between hand and object during interaction.
The proposed method includes two-stage randomized decision forest (RDF) with validation process, bilateral filtering, decision adjustment, and post-processing.
We demonstrate the effectiveness of the proposed method by testing for five objects.
The proposed method achieves the average F1 score of 0.8826 using different model for each object and 0.8645 using a global model for entire objects.
Also, the method takes only about 10ms to process each frame.
We believe that this is the state-of-the-art hand segmentation algorithm using depth map for hand-object interaction.