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Proceedings Paper

Recognition combined human pose tracking using single depth images
Author(s): Wonjun Kim; ByungIn Yoo; Jae-Joon Han; Changkyu Choi
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Paper 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.

Paper Details

Date Published: 17 February 2014
PDF: 6 pages
Proc. SPIE 9029, Visual Information Processing and Communication V, 90290E (17 February 2014); doi: 10.1117/12.2037644
Show Author Affiliations
Wonjun Kim, Samsung Advanced Institute of Technology (Korea, Republic of)
ByungIn Yoo, Samsung Advanced Institute of Technology (Korea, Republic of)
Jae-Joon Han, Samsung Advanced Institute of Technology (Korea, Republic of)
Changkyu Choi, Samsung Advanced Institute of Technology (Korea, Republic of)


Published in SPIE Proceedings Vol. 9029:
Visual Information Processing and Communication V
Amir Said; Onur G. Guleryuz; Robert L. Stevenson, Editor(s)

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