17 February 2014 Recognition combined human pose tracking using single depth images
Author Affiliations +
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.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wonjun Kim, ByungIn Yoo, Jae-Joon Han, 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
PROCEEDINGS
6 PAGES


SHARE
Back to Top