A Computational Framework for the Visual Correspondence Problem
Proceedings of the Eighth International Joint Conference on Artificial Intelligence. Vision. Pages 1043-1044.
Abstract
;I <'0111pu totional(rame 11 Vrk fo r solving th e visuol correspondence problem is JW' . \e/1/ed a11d l'valua / cd by u si11g a stochas l ic image model. The fram e1 vork dij.f'rrs principal~)' .fTom pr evio us work in !hat it em· phasizcs I he cumhi11a1ion of a lar ge cullcclion of independe11t measure · llll'nts. l' an ial derivwivcs of i ma gfs smootlli'd 1rilh a fl'lv different-sized Gaussian filt ers are sugges t ed as sui/able m eas uremc 11ts. A specific conJputalioll is shr>w n lo reliably es /ab lis h whflher or not two pointscurrespuml, pr o1 • idcd thai th e signal lo correspo11dencc noise ratio in the imag es tu be mmchcd exceeds two. The computation has been applied to anijicial and //a/Ural ima ges with encouraging r es ults.
@inproceedings{ijcai1983p241,
title = {A Computational Framework for the Visual Correspondence Problem},
author = {Kass, Michael},
booktitle = {Proceedings of the Eighth International Joint Conference on
Artificial Intelligence, {IJCAI-83}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Alan Bundy},
pages = {1043--1044},
year = {1983},
note = {Vision},
url = {https://ijcai.org/proceedings/1983/241},
}
TY - CPAPER TI - A Computational Framework for the Visual Correspondence Problem AU - Kass, Michael T2 - Proceedings of the Eighth International Joint Conference on Artificial Intelligence, IJCAI-83 PB - International Joint Conferences on Artificial Intelligence PY - 1983 SP - 1043 EP - 1044 UR - https://ijcai.org/proceedings/1983/241 ER -Copied
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