[1]ZHAO Jun,YU Jun,WANG Zengfu.Human motion tracking based on an improved inverse kinematics[J].CAAI Transactions on Intelligent Systems,2015,10(4):548-554.[doi:10.3969/j.issn.1673-4785.201403032]
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Human motion tracking based on an improved inverse kinematics

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 10 Number of periods: 2015 4 Page number: 548-554 Column: 学术论文—智能系统 Public date: 2015-08-25
Title:
Human motion tracking based on an improved inverse kinematics
Author(s):
ZHAO Jun1; 2;  YU Jun1; 2;  WANG Zengfu1; 2; 3
1. Department of Automation, University of Science and Technology of China, Hefei 230027, China;
2. National Laboratory of Speech and Language Information Processing, Hefei 230027, China;
3. Institute of Intelligent Machine, Chinese Academy of Sciences, Hefei 230027, China
Keywords:
improved inverse kinematics; human motion tracking; template matching; computer vision; user interface
CLC:
TH186
DOI:
10.3969/j.issn.1673-4785.201403032
Abstract:
With the rising demand for intelligent systems, the study of vision-based human motion is drawing the machine vision investigators, making it become the research focus of pattern recognition, behavioral science, behavior analyzing and processing. The existing algorithms have many kinds of restriction conditions, such as marking and camera calibration, not being able to meet people’s demand for tracking human motion. Therefore, this article proposes a human motion position tracking algorithm on the basis of video, combining the template matching and improved inverse kinematics. It first calculates the coarse position of joint point according to the inverse kinematics and forward kinematics, then applies template matching to each module of the appearing-model, and then determines the optimal location of joints and the 3D coordinates of joints, and finally obtains the 3D action sequences by reconstruction. Experimental results show that this algorithm can be close to and even reach the best level in both subjective visual feel and objective weighing standard in the field of human motion tracking.
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