ML Anthology

Shape and Appearance Context Modeling

Xiaogang Wang, Gianfranco Doretto, Thomas Sebastian, Jens Rittscher, Peter H. Tu
ICCV 2007 pp. 1-8
doi:10.1109/ICCV.2007.4409019 /iccv/2007/wang2007iccv-shape/

Abstract

In this work we develop appearance models for computing the similarity between image regions containing deformable objects of a given class in realtime. We introduce the concept of shape and appearance context. The main idea is to model the spatial distribution of the appearance relative to each of the object parts. Estimating the model entails computing occurrence matrices. We introduce a generalization of the integral image and integral histogram frameworks, and prove that it can be used to dramatically speed up occurrence computation. We demonstrate the ability of this framework to recognize an individual walking across a network of cameras. Finally, we show that the proposed approach outperforms several other methods.

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Cite

Text

Wang et al. "Shape and Appearance Context Modeling." IEEE/CVF International Conference on Computer Vision, 2007. doi:10.1109/ICCV.2007.4409019

Markdown

[Wang et al. "Shape and Appearance Context Modeling." IEEE/CVF International Conference on Computer Vision, 2007.](https://mlanthology.org/iccv/2007/wang2007iccv-shape/) doi:10.1109/ICCV.2007.4409019

BibTeX

@inproceedings{wang2007iccv-shape,
  title     = {{Shape and Appearance Context Modeling}},
  author    = {Wang, Xiaogang and Doretto, Gianfranco and Sebastian, Thomas and Rittscher, Jens and Tu, Peter H.},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2007},
  pages     = {1-8},
  doi       = {10.1109/ICCV.2007.4409019},
  url       = {https://mlanthology.org/iccv/2007/wang2007iccv-shape/}
}