Depth Discontinuities by Pixel-to-Pixel Stereo
International Journal of Computer Vision
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Tracking = Classification + Interpolation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Sign Recognition using Depth Image Streams
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Vision-based hand pose estimation: A review
Computer Vision and Image Understanding
A multi-view vision-based hand motion capturing system
Pattern Recognition
Hand gesture recognition using depth data
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Combining RGB and ToF cameras for real-time 3D hand gesture interaction
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
Tracking the articulated motion of two strongly interacting hands
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Generalised pose estimation using depth
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
Hi-index | 0.00 |
In this paper, we address the problem of hand posture recognition with a binocular camera. As bare hand has a few landmarks for matching, instead of using accurate matching between two views, we define a kind of mapping score---Disparity Cost Map. The disparity cost map serves as the final hand representation for recognition. As we use the disparity cost map, an explicit segmentation stage is not necessary. Local Binary Pattern (LBP) is used as feature for classification in this paper. In order to align the LBP feature, we further design an annular mask to deal with the problem of scaling, rotation, translation (RST) and search for an accurate bounding box of hand. The experimental results demonstrate the efficiency and robustness of our method. For 15 hand postures in varies cluttered background, the proposed method achieves an average recognition rate of 95% with a SVM classifier.