ML Anthology

A Statistical Method for 3D Object Detection Applied to Faces and Cars

Henry Schneiderman, Takeo Kanade
CVPR 2000 pp. 1746-1759
doi:10.1109/CVPR.2000.855895 /cvpr/2000/schneiderman2000cvpr-statistical/

Abstract

In this paper, we describe a statistical method for 3D object detection. We represent the statistics of both object appearance and "non-object" appearance using a product of histograms. Each histogram represents the joint statistics of a subset of wavelet coefficients and their position on the object. Our approach is to use many such histograms representing a wide variety of visual attributes. Using this method, we have developed the first algorithm that can reliably detect human faces with out-of-plane rotation and the first algorithm that can reliably detect passenger cars over a wide range of viewpoints.

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Cite

Text

Schneiderman and Kanade. "A Statistical Method for 3D Object Detection Applied to Faces and Cars." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2000. doi:10.1109/CVPR.2000.855895

Markdown

[Schneiderman and Kanade. "A Statistical Method for 3D Object Detection Applied to Faces and Cars." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2000.](https://mlanthology.org/cvpr/2000/schneiderman2000cvpr-statistical/) doi:10.1109/CVPR.2000.855895

BibTeX

@inproceedings{schneiderman2000cvpr-statistical,
  title     = {{A Statistical Method for 3D Object Detection Applied to Faces and Cars}},
  author    = {Schneiderman, Henry and Kanade, Takeo},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2000},
  pages     = {1746-1759},
  doi       = {10.1109/CVPR.2000.855895},
  url       = {https://mlanthology.org/cvpr/2000/schneiderman2000cvpr-statistical/}
}