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Human Body-Parts Tracking for Fine-Grained Behavior Classification
AbstractThis paper discusses the usefulness of human body-parts tracking for acquiring subtle cues in social interactions. While many kinds of body-parts tracking algorithms have been proposed, we focus on particle filtering-based tracking using prior models, which have several advantages for researches on social interactions. As a first step for extracting subtle cues from videos of social interaction behaviors, the advantages, disadvantages, and prospective properties of the body-parts tracking using prior models are summarized with actual results.
Related Material
[pdf][bibtex]@InProceedings{Ukita_2013_ICCV_Workshops,
author = {Norimichi Ukita and Atsushi Nakazawa},
title = {Human Body-Parts Tracking for Fine-Grained Behavior Classification},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {June},
year = {2013}
}
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