DocumentCode :
253790
Title :
Energy Based Multi-model Fitting & Matching for 3D Reconstruction
Author :
Isack, Hossam ; Boykov, Yuri
Author_Institution :
Univ. of Western Ontario, London, ON, Canada
fYear :
2014
fDate :
23-28 June 2014
Firstpage :
1146
Lastpage :
1153
Abstract :
Standard geometric model fitting methods take as an input a fixed set of feature pairs greedily matched based only on their appearances. Inadvertently, many valid matches are discarded due to repetitive texture or large baseline between view points. To address this problem, matching should consider both feature appearances and geometric fitting errors. We jointly solve feature matching and multi-model fitting problems by optimizing one energy. The formulation is based on our generalization of the assignment problem and its efficient min-cost-max-flow solver. Our approach significantly increases the number of correctly matched features, improves the accuracy of fitted models, and is robust to larger baselines.
Keywords :
feature extraction; geometry; image matching; image reconstruction; stereo image processing; 3D reconstruction; feature matching; multimodel fitting; multimodel matching; standard geometric model fitting methods; Computational modeling; Convergence; Estimation; Frequency modulation; Labeling; Optimization; Standards; assignment problem; dynamic MCMF; feature matching; flow recycling; model fitting; optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
Conference_Location :
Columbus, OH
Type :
conf
DOI :
10.1109/CVPR.2014.150
Filename :
6909546
Link To Document :
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