@inproceedings{c6b58101c47648508f0deb2332d261d6,
title = "A Bayesian multiple hypothesis approach to contour grouping",
abstract = "We present an approach to contour grouping based on classical tracking techniques. Edge points are segmented into smooth curves so as to minimize a recursively updated Bayesian probability measure. The resulting algorithm employs local smoothness constraints and a statistical description of edge detection, and can accurately handle corners, bifurcations, and curve intersections. Experimental results demonstrate good performance.",
author = "Cox, {Ingemar J.} and Rehg, {James M.} and Sunita Hingorani",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1992.; 2nd European Conference on Computer Vision, ECCV 1992 ; Conference date: 19-05-1992 Through 22-05-1992",
year = "1992",
doi = "10.1007/3-540-55426-2_9",
language = "English (US)",
isbn = "9783540554264",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "72--77",
editor = "Giulio Sandini",
booktitle = "Computer Vision - ECCV 1992 - 2nd European Conference on Computer Vision, Proceedings",
address = "Germany",
}