Title :
Multiple unordered wide-baseline image matching and grouping
Author :
He, Zhoucan ; Wang, Qing ; Yang, Heng
Author_Institution :
Sch. of Comput. Sci. & Eng., Northwestern Polytech. Univ., Xi´´an, China
fDate :
June 28 2009-July 3 2009
Abstract :
This paper focuses on the multi-view feature matching problem from unordered image sets. Firstly, an efficient and effective high dimensional feature matching algorithm is proposed, so called ELSH (extended local sensitive hash), which can significantly improve matching accuracy at fast speed. Secondly, a novel unsupervised image grouping strategy is proposed to cluster the unordered images into content-related group, which does not normally require any other constraints. Extensive experimental results have shown that our method can obtain better performance than the classical algorithms in tackling multi-view matching problem.
Keywords :
feature extraction; image matching; pattern clustering; unsupervised learning; content-related group; extended local sensitive hash; multiple wide-baseline image matching; multiview feature matching problem; unordered image clustering; unsupervised image grouping strategy; Clustering algorithms; Computer science; Computer vision; Helium; Image matching; Indexing; Nearest neighbor searches; Robustness; Search methods; Search problems; KNN (K nearest neighbor) search; extended LSH; image grouping; multi-view matching;
Conference_Titel :
Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on
Conference_Location :
New York, NY
Print_ISBN :
978-1-4244-4290-4
Electronic_ISBN :
1945-7871
DOI :
10.1109/ICME.2009.5202590