Detection of humans and estimation of their 2D poses from a single image are challenging tasks. This is especially true when part of the observation is occluded. However, given a limited class of movements, poses can be recovered given the visible body-parts. To this end, we propose a novel template representation where the body is divided into five body-parts. Given a match, we not only estimate the joints in the body-part, but all joints in the body. Quantitative evaluation on a HumanEva walking sequence shows mean 2D errors of approximately 27.5 pixels. For simulated occlusion of the head and arms, similar results are obtained while occlusion of the legs increases this error by 6 pixels.
|Title of host publication||Proceedings of the International Conference on Articulated Motion and Deformable Objects (AMDO)|
|Editors||F.J. Perales, R.B. Fisher|
|Place of Publication||Berlin|
|Number of pages||10|
|Publication status||Published - 27 Jun 2008|
|Name||Lecture Notes in Computer Science|
- EC Grant Agreement nr.: FP6/033812