TY - GEN
T1 - Joint tracking and gait recognition of multiple people in video
AU - Babaee, Maryam
AU - Rigoll, Gerhard
AU - Babaee, Mohammadreza
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - We propose a novel approach to address the problem of jointly tracking and gait recognition of multiple people in a video sequence. The most state of the art algorithms for gait recognition consider the cases where there is only one person without any occlusion in a very constrained environment. However, in real scenarios such as in airports, train stations, etc, there are many people in the environment that make these algorithms inapplicable. Although first tracking of each person and then gait recognition could be a solution, we argue that the multi-people tracking and the gait recognition in a video are two sub-problems that can help each other. Hence, we propose a joint tracking and gait recognition of multiple people as one framework that can improve gait recognition accuracy and decrease the ID switching in tracking. Experimental results confirm the validity of proposed approach.
AB - We propose a novel approach to address the problem of jointly tracking and gait recognition of multiple people in a video sequence. The most state of the art algorithms for gait recognition consider the cases where there is only one person without any occlusion in a very constrained environment. However, in real scenarios such as in airports, train stations, etc, there are many people in the environment that make these algorithms inapplicable. Although first tracking of each person and then gait recognition could be a solution, we argue that the multi-people tracking and the gait recognition in a video are two sub-problems that can help each other. Hence, we propose a joint tracking and gait recognition of multiple people as one framework that can improve gait recognition accuracy and decrease the ID switching in tracking. Experimental results confirm the validity of proposed approach.
KW - Gait recognition
KW - Multi-people tracking
UR - http://www.scopus.com/inward/record.url?scp=85045293825&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2017.8296751
DO - 10.1109/ICIP.2017.8296751
M3 - Conference contribution
AN - SCOPUS:85045293825
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 2592
EP - 2596
BT - 2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
PB - IEEE Computer Society
T2 - 24th IEEE International Conference on Image Processing, ICIP 2017
Y2 - 17 September 2017 through 20 September 2017
ER -