Image Retargeting for Preserving Robust Local Feature: Application to Mobile Visual Search
Abstract: With the sharp increasing of mobile devices, conducting search on mobile devices becomes pervasive, and one of the most popular applications is mobile visual search. To achieve low bit-rate visual search, most of the existing works focus on addressing local descriptor coding and BoW histogram compression . In this paper, we extend the concept of image retargeting and propose a new image resizing approach that is devoted to preserving the robust local features in the query image while resizing it. Based on the extended concept, we introduce a novel mobile-visual-search scheme that conducts the proposed approach to reduce the size of the query image for achieving low bit-rate visual search. Extensive experiments on Oxford 5 K and Flickr 100k datasets show that our approach obtains superior retrieval performance than state-of-the-art image resizing approaches at the similar query size; meanwhile, it is cost effective in terms of processing time.