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Proceedings Paper

Image categorization based on multi-scale vocabulary
Author(s): Xin Yang; Jinhui Tang; Xiuqing Wu
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Paper Abstract

Nowadays, local feature based image categorization algorithm has attracted increasing attention in the computer vision community. In this paper, we present a local feature based image categorization scheme by using Multi-Scale Vocabulary. This technique works by partitioning the feature space into clusters at several different levels to form multi-scale vocabulary and generate corresponding fixed-length descriptors at different scales for each image. Then we design particular similarity measure for multi-scale descriptors and finally apply KNN and SVM to realize image categorization task. Experiments conducted on the ETH80 dataset have demonstrated the effectiveness of our approach.

Paper Details

Date Published: 15 November 2007
PDF: 6 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67881F (15 November 2007); doi: 10.1117/12.749679
Show Author Affiliations
Xin Yang, Univ. of Science and Technology of China (China)
Jinhui Tang, Univ. of Science and Technology of China (China)
Xiuqing Wu, Univ. of Science and Technology of China (China)


Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision

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