Justin Domke, Yiannis Aloimonos Computer Vision Laboratory, Dept. of Computer ...  Home/Search
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Abstract: This paper is an argument for two assertions: First, that by representing correspondence probabilistically, drastically more correspondence information can be extracted from images. Second, that by increasing the amount of correspondence information used, more accurate egomotion estimation is possible. We present a novel approach illustrating these principles. (Update)
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BibTeX entry: (Update)
@misc{ yiannis-probabilistic,
author = "Justin Domke Yiannis",
title = "A Probabilistic Framework for Correspondence and Egomotion",
url = "citeseer.ist.psu.edu/746641.html" }
Citations (may not include all citations):353 A combined corner and edge detector (context) - Harris, Stephens - 1988
242 Vision: a computational investigation into the human represe.. (context) - Marr - 1982
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103 Probability distributions of optical flow - Simoncelli, Adelson et al. - 1991
72 Stereo disparity computation using gabor filters (context) - Sanger - 1988
56 Distinctive image features from scale-invariant keypoints - Lowe - 2004
31 A critique of structure-from-motion algorithms - Oliensis - 2000
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