Energy Based Multi-model Fitting & Matching for 3D Reconstruction

Hossam Isack, Yuri Boykov; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014, pp. 1146-1153

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.

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[bibtex]
@InProceedings{Isack_2014_CVPR,
author = {Isack, Hossam and Boykov, Yuri},
title = {Energy Based Multi-model Fitting & Matching for 3D Reconstruction},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2014}
}