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|Title:||A fast algorithm for creating a compact and discriminative visual codebook|
|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 Place:||New York|
|Series/Report no.:||Lecture Notes in Computer Science; Vol. 5305|
|Conference Name:||European Conference on Computer Vision (ECCV) (10th : 2008 : Marseille, France)|
|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|
|Appears in Collections:||Aurora harvest 5|
Computer Science publications
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