Recognition of Repetitive Sequential Human Activity

Quanfu Fan, Russell Bobbitt, Yun Zhai, Akira Yanagawa, Sharath Pankanti, Arun Hampapur

CVPR 2009 pp. 943-950

doi:10.1109/CVPR.2009.5206644 /cvpr/2009/fan2009cvpr-recognition/

Abstract

We present a novel framework for recognizing repetitive sequential events performed by human actors with strong temporal dependencies and potential parallel overlap. Our solution incorporates sub-event (or primitive) detectors and a spatiotemporal model for sequential event changes. We develop an effective and efficient method to integrate primitives into a set of sequential events where strong temporal constraints are imposed on the ordering of the primitives. In particular, the combination process is approached as an optimization problem. A specialized Viterbi algorithm is designed to learn and infer the target sequential events and handle the event overlap simultaneously. To demonstrate the effectiveness of the proposed framework, we report detailed quantitative analysis on a large set of cashier checkout activities in a retail store.

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Cite

Text

Fan et al. "Recognition of Repetitive Sequential Human Activity." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009. doi:10.1109/CVPR.2009.5206644

Markdown

[Fan et al. "Recognition of Repetitive Sequential Human Activity." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009.](https://mlanthology.org/cvpr/2009/fan2009cvpr-recognition/) doi:10.1109/CVPR.2009.5206644

BibTeX

@inproceedings{fan2009cvpr-recognition,
  title     = {{Recognition of Repetitive Sequential Human Activity}},
  author    = {Fan, Quanfu and Bobbitt, Russell and Zhai, Yun and Yanagawa, Akira and Pankanti, Sharath and Hampapur, Arun},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2009},
  pages     = {943-950},
  doi       = {10.1109/CVPR.2009.5206644},
  url       = {https://mlanthology.org/cvpr/2009/fan2009cvpr-recognition/}
}