Model-based gait representation via spatial point reconstruction |
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Authors: | Yuan-yuan Zhang Xiao-juan Wu Qiu-qi Ruan |
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Institution: | (1) Institute of Image Processing and Pattern Recognition, Shandong University, Jinan, 250100, China;(2) Institute of Information Science, Beijing Jiaotong University, Beijing, 100044, China |
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Abstract: | This paper proposed a novel model-based feature representation method to characterize human walking properties for individual
recognition by gait. First, a new spatial point reconstruction approach is proposed to recover the coordinates of 3D points
from 2D images by the related coordinate conversion factor (CCF). The images are captured by a monocular camera. Second, the
human body is represented by a connected three-stick model. Then the parameters of the body model are recovered by the method
of projective geometry using the related CCF. Finally, the gait feature composed of those parameters is defined, and it is
proved by experiments that those features can partially avoid the influence of viewing angles between the optical axis of
the camera and walking direction of the subject.
Foundation item: the National Natural Science Foundation of China (No. 60675024) |
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Keywords: | coordinate conversion factor (CCF) gait feature monocular camera parallel restriction |
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