Robust gait-based gender classification using depth cameras
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TLDR
A new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle that improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information.Abstract:
This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section.read more
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References
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Proceedings ArticleDOI
Real-time human pose recognition in parts from single depth images
Jamie Shotton,Andrew Fitzgibbon,Mat Cook,Toby Sharp,Mark J. Finocchio,Richard E. Moore,Alex Aben-Athar Kipman,Andrew Blake +7 more
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Real-time human pose recognition in parts from single depth images
Jamie Shotton,Toby Sharp,Alex Aben-Athar Kipman,Andrew Fitzgibbon,Mark J. Finocchio,Andrew Blake,Mat Cook,Richard Moore +7 more
TL;DR: This work takes an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler per-pixel classification problem, and generates confidence-scored 3D proposals of several body joints by reprojecting the classification result and finding local modes.
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Proceedings ArticleDOI
A Framework for Evaluating the Effect of View Angle, Clothing and Carrying Condition on Gait Recognition
Shiqi Yu,Daoliang Tan,Tieniu Tan +2 more
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