ML Anthology

Shape Band: A Deformable Object Detection Approach

Xiang Bai, Quannan Li, Longin Jan Latecki, Wenyu Liu, Zhuowen Tu
CVPR 2009 pp. 1335-1342
doi:10.1109/CVPR.2009.5206543 /cvpr/2009/bai2009cvpr-shape/

Abstract

In this paper, we focus on the problem of detecting/matching a query object in a given image. We propose a new algorithm, shape band, which models an object within a bandwidth of its sketch/contour. The features associated with each point on the sketch are the gradients within the bandwidth. In the detection stage, the algorithm simply scans an input image at various locations and scales for good candidates. We then perform fine scale shape matching to locate the precise object boundaries, also by taking advantage of the information from the shape band. The overall algorithm is very easy to implement, and our experimental results show that it can outperform stat-of-the-art contour based object detection algorithms.

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Text

Bai et al. "Shape Band: A Deformable Object Detection Approach." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009. doi:10.1109/CVPR.2009.5206543

Markdown

[Bai et al. "Shape Band: A Deformable Object Detection Approach." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009.](https://mlanthology.org/cvpr/2009/bai2009cvpr-shape/) doi:10.1109/CVPR.2009.5206543

BibTeX

@inproceedings{bai2009cvpr-shape,
  title     = {{Shape Band: A Deformable Object Detection Approach}},
  author    = {Bai, Xiang and Li, Quannan and Latecki, Longin Jan and Liu, Wenyu and Tu, Zhuowen},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2009},
  pages     = {1335-1342},
  doi       = {10.1109/CVPR.2009.5206543},
  url       = {https://mlanthology.org/cvpr/2009/bai2009cvpr-shape/}
}