ML Anthology

Fusion-Based Background-Subtraction Using Contour Saliency

James W. Davis, Vinay Sharma
CVPR 2005 pp. 11
doi:10.1109/CVPR.2005.462 /cvpr/2005/davis2005cvpr-fusion/

Abstract

We present a new contour-based background-subtraction technique using thermal and visible imagery for persistent object detection in urban settings. Statistical backgroundsubtraction in the thermal domain is used to identify the initial regions-of-interest. Color and intensity information are used within these areas to obtain the corresponding regionsof- interest in the visible domain. Within each region, input and background gradient information are combined to form a Contour Saliency Map. The binary contour fragments, obtained from corresponding Contour Saliency Maps, are then combined. An A path-constrained search along watershed boundaries is used to complete and close any broken contour segments. Lastly, the contour image is flood- filled to produce silhouettes. Results of our approach are presented and compared against manually segmented data.

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Cite

Text

Davis and Sharma. "Fusion-Based Background-Subtraction Using Contour Saliency." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.462

Markdown

[Davis and Sharma. "Fusion-Based Background-Subtraction Using Contour Saliency." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/davis2005cvpr-fusion/) doi:10.1109/CVPR.2005.462

BibTeX

@inproceedings{davis2005cvpr-fusion,
  title     = {{Fusion-Based Background-Subtraction Using Contour Saliency}},
  author    = {Davis, James W. and Sharma, Vinay},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2005},
  pages     = {11},
  doi       = {10.1109/CVPR.2005.462},
  url       = {https://mlanthology.org/cvpr/2005/davis2005cvpr-fusion/}
}