Recognition combined human pose tracking using single depth images

Wonjun Kim; ByungIn Yoo; Jae-Joon Han; Changkyu Choi

doi:10.1117/12.2037644

17 February 2014 Recognition combined human pose tracking using single depth images

Wonjun Kim, ByungIn Yoo, Jae-Joon Han, Changkyu Choi

Proceedings Volume 9029, Visual Information Processing and Communication V; 90290E (2014) https://doi.org/10.1117/12.2037644
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

This paper presents a method for tracking human poses in real-time from depth image sequences. The key idea is to adopt recognition for generating the model to be tracked. In contrast to traditional methods utilizing a single-typed 3D body model, we directly define the human body model based on the body part recognition result of the captured depth image, which leads to the reliable tracking regardless of users' appearances. Moreover, the proposed method has the ability to efficiently reduce the tracking drift by exploiting the joint information inserted into our body model. Experimental results on real-world environments show that the proposed method is effective for estimating various human poses in real-time.

Citation Download Citation

Wonjun Kim, ByungIn Yoo, Jae-Joon Han, and Changkyu Choi "Recognition combined human pose tracking using single depth images", Proc. SPIE 9029, Visual Information Processing and Communication V, 90290E (17 February 2014); https://doi.org/10.1117/12.2037644

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