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.
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