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


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