ML Anthology

Human Body-Parts Tracking for Fine-Grained Behavior Classification

Norimichi Ukita, Atsushi Nakazawa
ICCVW 2013 pp. 777-778
doi:10.1109/ICCVW.2013.106 /iccvw/2013/ukita2013iccvw-human/

Abstract

This 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.

ICCVW Semantic Scholar

Cite

Text

Ukita and Nakazawa. "Human Body-Parts Tracking for Fine-Grained Behavior Classification." IEEE/CVF International Conference on Computer Vision Workshops, 2013. doi:10.1109/ICCVW.2013.106

Markdown

[Ukita and Nakazawa. "Human Body-Parts Tracking for Fine-Grained Behavior Classification." IEEE/CVF International Conference on Computer Vision Workshops, 2013.](https://mlanthology.org/iccvw/2013/ukita2013iccvw-human/) doi:10.1109/ICCVW.2013.106

BibTeX

@inproceedings{ukita2013iccvw-human,
  title     = {{Human Body-Parts Tracking for Fine-Grained Behavior Classification}},
  author    = {Ukita, Norimichi and Nakazawa, Atsushi},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2013},
  pages     = {777-778},
  doi       = {10.1109/ICCVW.2013.106},
  url       = {https://mlanthology.org/iccvw/2013/ukita2013iccvw-human/}
}