Multi-view feature matching and image grouping from multiple unordered wide-baseline images

Xiuyuan Zeng; Heng Yang; Qing Wang

doi:10.1007/978-3-540-89646-3_40

Multi-view feature matching and image grouping from multiple unordered wide-baseline images

Xiuyuan Zeng, Heng Yang, Qing Wang

School of Computer Science

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Advances in Visual Computing - 4th International Symposium, ISVC 2008, Proceedings
Pages	410-419
Number of pages	10
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-540-89646-3_40
State	Published - 2008
Event	4th International Symposium on Visual Computing, ISVC 2008 - Las Vegas, NV, United States Duration: 1 Dec 2008 → 3 Dec 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	5359 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Symposium on Visual Computing, ISVC 2008
Country/Territory	United States
City	Las Vegas, NV
Period	1/12/08 → 3/12/08

Access to Document

10.1007/978-3-540-89646-3_40

Cite this

Zeng, X., Yang, H., & Wang, Q. (2008). Multi-view feature matching and image grouping from multiple unordered wide-baseline images. In Advances in Visual Computing - 4th International Symposium, ISVC 2008, Proceedings (PART 2 ed., pp. 410-419). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5359 LNCS, No. PART 2). https://doi.org/10.1007/978-3-540-89646-3_40

Zeng, Xiuyuan ; Yang, Heng ; Wang, Qing. / Multi-view feature matching and image grouping from multiple unordered wide-baseline images. Advances in Visual Computing - 4th International Symposium, ISVC 2008, Proceedings. PART 2. ed. 2008. pp. 410-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{2b93b44a0f5a455088f69fdc7420c031,

title = "Multi-view feature matching and image grouping from multiple unordered wide-baseline images",

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.",

author = "Xiuyuan Zeng and Heng Yang and Qing Wang",

year = "2008",

doi = "10.1007/978-3-540-89646-3_40",

language = "英语",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 2",

pages = "410--419",

booktitle = "Advances in Visual Computing - 4th International Symposium, ISVC 2008, Proceedings",

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note = "4th International Symposium on Visual Computing, ISVC 2008 ; Conference date: 01-12-2008 Through 03-12-2008",

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Zeng, X, Yang, H & Wang, Q 2008, Multi-view feature matching and image grouping from multiple unordered wide-baseline images. in Advances in Visual Computing - 4th International Symposium, ISVC 2008, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5359 LNCS, pp. 410-419, 4th International Symposium on Visual Computing, ISVC 2008, Las Vegas, NV, United States, 1/12/08. https://doi.org/10.1007/978-3-540-89646-3_40

Multi-view feature matching and image grouping from multiple unordered wide-baseline images. / Zeng, Xiuyuan; Yang, Heng; Wang, Qing.
Advances in Visual Computing - 4th International Symposium, ISVC 2008, Proceedings. PART 2. ed. 2008. p. 410-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5359 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Zeng X, Yang H, Wang Q. Multi-view feature matching and image grouping from multiple unordered wide-baseline images. In Advances in Visual Computing - 4th International Symposium, ISVC 2008, Proceedings. PART 2 ed. 2008. p. 410-419. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-540-89646-3_40

Multi-view feature matching and image grouping from multiple unordered wide-baseline images

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