A. Berg, and J. Malik. Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings
of the 2001 IEEE Computer Society Conf. on, 1, page I----607----I----614 vol.1. (2001)
DOI: 10.1109/CVPR.2001.990529
Abstract
We address the problem of finding point correspondences in images
by way of an approach to template matching that is robust under affine
distortions. This is achieved by applying ``geometric blur'' to both
the template and the image, resulting in a fall-off in similarity
that is close to linear in the norm of the distortion between the
template and the image. Results in wide baseline stereo correspondence,
face detection, and feature correspondence are included.
%0 Conference Paper
%1 Berg2001
%A Berg, A C
%A Malik, J
%B Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings
of the 2001 IEEE Computer Society Conf. on
%D 2001
%K affine baseline blur, correspondence, correspondence,computer correspondences, detection, distortions, face feature geometric image matching, point recognition, stereo template transforms vision wide
%P I----607----I----614 vol.1
%R 10.1109/CVPR.2001.990529
%T Geometric blur for template matching
%V 1
%X We address the problem of finding point correspondences in images
by way of an approach to template matching that is robust under affine
distortions. This is achieved by applying ``geometric blur'' to both
the template and the image, resulting in a fall-off in similarity
that is close to linear in the norm of the distortion between the
template and the image. Results in wide baseline stereo correspondence,
face detection, and feature correspondence are included.
@inproceedings{Berg2001,
abstract = { We address the problem of finding point correspondences in images
by way of an approach to template matching that is robust under affine
distortions. This is achieved by applying ``geometric blur'' to both
the template and the image, resulting in a fall-off in similarity
that is close to linear in the norm of the distortion between the
template and the image. Results in wide baseline stereo correspondence,
face detection, and feature correspondence are included.},
added-at = {2013-09-29T14:16:50.000+0200},
author = {Berg, A C and Malik, J},
biburl = {https://www.bibsonomy.org/bibtex/24ee14c8ec6d50b0dc4282a7c3a7d982e/guillem.palou},
booktitle = {Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings
of the 2001 IEEE Computer Society Conf. on},
doi = {10.1109/CVPR.2001.990529},
interhash = {68c3701602e74b07f2fbf38df5d4620b},
intrahash = {4ee14c8ec6d50b0dc4282a7c3a7d982e},
issn = {1063-6919},
keywords = {affine baseline blur, correspondence, correspondence,computer correspondences, detection, distortions, face feature geometric image matching, point recognition, stereo template transforms vision wide},
pages = {I----607----I----614 vol.1},
timestamp = {2013-09-29T14:16:50.000+0200},
title = {{Geometric blur for template matching}},
volume = 1,
year = 2001
}