A Bag-of-Regions approach to Sketch-based Image Retrieval

Abstract

This paper presents a sketch-based image retrieval system using a bag-of-region representation of images. Regions from the nodes of a hierarchical region tree range in various scales of details. They have appealing properties for object level inference such as the naturally encoded shape and scale information of objects and the specified domains on which to compute features without being affected by clutter from outside the region. The proposed approach builds shape descriptor on the salient shape among the clutters and thus yields significant performance improvements over the previous results on three leading descriptors in Bag-of-Words framework for sketch based image retrieval. Matched region also facilitates the localization of sketched object within the retrieved image.

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