Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/67359
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Type: Conference paper
Title: A fast algorithm for creating a compact and discriminative visual codebook
Author: Wang, L.
Zhou, L.
Shen, C.
Citation: Proceedings of 10th European Conference on Computer Vision (ECCV), 12-18 October, 2008 / D. Forsyth, P. Torr and A. Zisserman (eds.); Part IV, pp.719-732
Publisher: Springer
Publisher Place: New York
Issue Date: 2008
Series/Report no.: Lecture Notes in Computer Science; Vol. 5305
ISBN: 3540886923
9783540886921
ISSN: 0302-9743
1611-3349
Conference Name: European Conference on Computer Vision (ECCV) (10th : 2008 : Marseille, France)
Statement of
Responsibility: 
Lei Wang, Luping Zhou and Chunhua Shen
Abstract: In patch-based object recognition, using a compact visual codebook can boost computational efficiency and reduce memory cost. Nevertheless, compared with a large-sized codebook, it also risks the loss of discriminative power. Moreover, creating a compact visual codebook can be very time-consuming, especially when the number of initial visual words is large. In this paper, to minimize its loss of discriminative power, we propose an approach to build a compact visual codebook by maximally preserving the separability of the object classes. Furthermore, a fast algorithm is designed to accomplish this task effortlessly, which can hierarchically merge 10,000 visual words down to 2 in ninety seconds. Experimental study shows that the compact visual codebook created in this way can achieve excellent classification performance even after a considerable reduction in size. © 2008 Springer Berlin Heidelberg.
Rights: © Springer, Part of Springer Science+Business Media
DOI: 10.1007/978-3-540-88693-8_53
Appears in Collections:Aurora harvest 5
Computer Science publications

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