Research on dynamic human object tracking algorithm

Authors:
Yongjian He;Qiong Wu;Shoupeng Feng;Rongkun Zhou;Yonghua Xing;Fei Wang
Affiliations:
Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China and Xi'an Communication Institute, Xi'an, China;Xi'an Communication Institute, Xi'an, China;Xi'an Communication Institute, Xi'an, China;Xi'an Communication Institute, Xi'an, China;Xi'an Communication Institute, Xi'an, China;Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Year:
2011

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Abstract

This paper studies the dynamic human object tracking problem. Under the condition of both of the camera and the object being tracked simultaneously move, when the movement of the object is too fast and the speeds of the two do not match, the tracking of the moving object will have lag issues. This paper presents an improved particle-tracking method. The method, during the tracking process, can reduce the number of particles online according to the actual tracking situation, thereby reducing computation time, so that the computing speed can be adjusted in real time according to the velocity of the being-tracked object to form the best match of the speeds. Experimental results show that the improved algorithm well solves the lag problems of the moving object being tracked and the tracking performance is significantly improved.