Document Type
Article
Publication Date
11-2011
Publication Title
Machine Vision and Applications
Abstract
The advent of the HumanEva standardized motion capture data sets has enabled quantitative evaluation of motion capture algorithms on comparable terms. This paper measures the performance of an existing monocular recognition-based pose recovery algorithm on select HumanEva data, including all the HumanEva II clips. The method uses a physically-motivated Markov process to connect adajacent frames and achieve a 3D relative mean error of 8.9 cm per joint. It further investigates factors contributing to the error, and finds that research into better pose retrieval methods offers promise for improvement of this technique and those related to it. Finally, it investigates the effects of local search optimization with the same recognition-based algorithm and finds no significant deterioration in the results, indicating that processing speed can be largely independent of the size of the recognition library for this approach.
Volume
22
Issue
6
First Page
995
Last Page
1008
DOI
10.1007/s00138-011-0344-x
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Rights
© Nick Howe
Recommended Citation
Howe, Nicholas, "A Recognition-Based Motion Capture Baseline on the HumanEva II Test Data" (2011). Computer Science: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/csc_facpubs/125
Comments
Author’s submitted manuscript.