ML Anthology

People Detection in Low Resolution Infrared Videos

Roland Miezianko, Dragoljub Pokrajac
CVPRW 2008 pp. 1-6
doi:10.1109/CVPRW.2008.4563056 /cvprw/2008/miezianko2008cvprw-people/

Abstract

In this paper we present a method for detecting people in low resolution infrared videos. We further explore the feature set based on histogram of gradients beyond the well received HOG descriptors. Our approach is based on extracting gradient histograms from recursively generated patches and subsequently computing histogram ratios between the patches. Each set of patches is defined in terms of relative position within the search window, and each set is then recursively applied to extract smaller patches. The histogram of gradient ratios between patches become the feature vector. We adopted a linear SVM classifier as it provides a fast and effective framework for feature descriptor processing with minimal parameter tuning. Experimental results are presented on various OTCBVS datasets.

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Cite

Text

Miezianko and Pokrajac. "People Detection in Low Resolution Infrared Videos." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4563056

Markdown

[Miezianko and Pokrajac. "People Detection in Low Resolution Infrared Videos." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/miezianko2008cvprw-people/) doi:10.1109/CVPRW.2008.4563056

BibTeX

@inproceedings{miezianko2008cvprw-people,
  title     = {{People Detection in Low Resolution Infrared Videos}},
  author    = {Miezianko, Roland and Pokrajac, Dragoljub},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2008},
  pages     = {1-6},
  doi       = {10.1109/CVPRW.2008.4563056},
  url       = {https://mlanthology.org/cvprw/2008/miezianko2008cvprw-people/}
}