Performance analysis for automated gait extraction and recognition in multi-camera surveillance |
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Authors: | Michela Goffredo Imed Bouchrika John N Carter Mark S Nixon |
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Affiliation: | (1) School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK |
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Abstract: | Many studies have confirmed that gait analysis can be used as a new biometrics. In this research, gait analysis is deployed
for people identification in multi-camera surveillance scenarios. We present a new method for viewpoint independent markerless
gait analysis that does not require camera calibration and works with a wide range of walking directions. These properties
make the proposed method particularly suitable for gait identification in real surveillance scenarios where people and their
behaviour need to be tracked across a set of cameras. Tests on 300 synthetic and real video sequences, with subjects walking
freely along different walking directions, have been performed. Since the choice of the cameras’ characteristics is a key-point
for the development of a smart surveillance system, the performance of the proposed approach is measured with respect to different
video properties: spatial resolution, frame-rate, data compression and image quality. The obtained results show that markerless
gait analysis can be achieved without any knowledge of camera’s position and subject’s pose. The extracted gait parameters
allow recognition of people walking from different views with a mean recognition rate of 92.2% and confirm that gait can be
effectively used for subjects’ identification in a multi-camera surveillance scenario. |
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Keywords: | |
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