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Appearance Matching of Occluded Objects Using Coarse-to-Fine Adaptive Masks

Jeff L. Edwards, Hiroshi Murase
CVPR 1997 pp. 533-539
doi:10.1109/CVPR.1997.609377 /cvpr/1997/edwards1997cvpr-appearance/

Abstract

In this paper, we discuss an appearance matching technique for the interpretation of color scenes containing occluded objects. Dealing with occlusions is very difficult, and we have explored the use of an iterative, coarse-to-fine correlation-based method that uses hypothesized occlusion events to modify the scene-to-template similarity measure at run-time. Specifically, a binary mask is used to adaptively exclude regions of the template image from the correlation computation. At each iteration, these masks are adjusted based on higher resolution scene data and the occluding interactions between multiple object hypotheses. We present results which demonstrate the technique is reasonably robust over a large database of color test scenes containing objects at a variety of scales, and tolerates minor object rotations and global illumination variations.

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Cite

Text

Edwards and Murase. "Appearance Matching of Occluded Objects Using Coarse-to-Fine Adaptive Masks." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997. doi:10.1109/CVPR.1997.609377

Markdown

[Edwards and Murase. "Appearance Matching of Occluded Objects Using Coarse-to-Fine Adaptive Masks." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997.](https://mlanthology.org/cvpr/1997/edwards1997cvpr-appearance/) doi:10.1109/CVPR.1997.609377

BibTeX

@inproceedings{edwards1997cvpr-appearance,
  title     = {{Appearance Matching of Occluded Objects Using Coarse-to-Fine Adaptive Masks}},
  author    = {Edwards, Jeff L. and Murase, Hiroshi},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1997},
  pages     = {533-539},
  doi       = {10.1109/CVPR.1997.609377},
  url       = {https://mlanthology.org/cvpr/1997/edwards1997cvpr-appearance/}
}