A 3-D Depth Information Based Human Motion Pose Tracking Algorithms

• Published in: Sensors & transducers Vol. 174; no. 7; p. 253
• Main Authors: Yang, Kai, Wei, Benzheng, Wang, Qingxiang, Ren, Xiaoqiang, Xu, Yunfeng, Liu, Huaihui
• Format: Journal Article
• Language: English
• Published: Toronto IFSA Publishing, S.L 01.07.2014
• Subjects: Accuracy; Advantages; Algorithms; Cameras; Computer animation; Human body; Human motion; Light; Methods; Technological change; Three dimensional; Tracking; Transducers; Vision
• ISSN: 2306-8515; 1726-5479

Tracking human pose is a critical step on recognizing and analyzing the human motion on 3-D stereo vision, and it has a great value and potential for applications of the machine vision. However, due to the complexity of human motion and background, most of the existing tracking methods for 3-D human motion gesture will add some extra restrictions on acquiring the human motion, and the tracking algorithms are often hard to obtain robust algorithm performance. In this paper, a new human motion tracking method based on 3-D depth information is presented aiming to improve the tracking method quality. The algorithm determines the human body contour through analyzing the depth image information at first. Then the special skeletal points are estimated and tracked based on the 3-D depth vision images. Finally, the motion estimation is executed by using the three-step search algorithm, and the tracking pose is achieved naturally. Experimental results show the effectiveness of the algorithm, and it also has verified method feasibility and superiority on the aspect of acquiring human motion gestures compared to the similar method.