Multi-view Feature Matching and Image Grouping from Multiple Unordered Wide-Baseline Images

Authors:
Xiuyuan Zeng;Heng Yang;Qing Wang
Affiliations:
School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, P. R. China 710072;School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, P. R. China 710072;School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, P. R. China 710072
Venue:
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Year:
2008

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Abstract

In this paper, we present a photo grouping method in multi-view feature matching problem, especially from multiple unordered wide-baseline images. By analyzing and comparing the connections between images with undirected weighted graph, we abstract the photo grouping into a nonlinear optimization problem and tackle it by using an annealing based method. Additionally, a new high-dimensional feature searching algorithm is also developed to find out the initial features matching number more robustly, which is used to be the measurement of image relativities in the grouping algorithm. Finally, we show the analyses and discussions of the performance of the proposed method and experimental results have proven that the novel approach is more efficient than the traditional ones.