Extended abstract for CVPR 2007 workshop on Evaluating Human Motion
Quantitative comparison of algorithms for human motion capture have been hindered by the lack of standard benchmarks. The development of the HumanEva I & II test sets provides an opportunity to assess the state of the art by evaluating existing methods on the new standardized test videos. This paper presents a comprehensive evaluation of a monocular recognition-based pose recovery algorithm on the HumanEva II clips. The results show that the method achieves a mean relative error of around 10-12 cm per joint.
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© Nicholas Howe
Howe, Nicholas, "Recognition-Based Motion Capture and the HumanEva II Test Data" (2007). Computer Science: Faculty Publications, Smith College, Northampton, MA.