Highly Efficient Mobile Visual Search Algorithm

Chuang ZHU  Xiao Feng HUANG  Guo Qing XIANG  Hui Hui DONG  Jia Wen SONG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.12   pp.3073-3082
Publication Date: 2018/12/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDP7075
Type of Manuscript: PAPER
Category: Data Engineering, Web Information Systems
Keyword: 
mobile visual search,  descriptor extraction,  feature selection,  reranking,  

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Summary: 
In this paper, we propose a highly efficient mobile visual search algorithm. For descriptor extraction process, we propose a low complexity feature detection which utilizes the detected local key points of the coarse octaves to guide the scale space construction and feature detection in the fine octave. The Gaussian and Laplacian operations are skipped for the unimportant area, and thus the computing time is saved. Besides, feature selection is placed before orientation computing to further reduce the complexity of feature detection by pre-discarding some unimportant local points. For the image retrieval process, we design a high-performance reranking method, which merges both the global descriptor matching score and the local descriptor similarity score (LDSS). In the calculating of LDSS, the tf-idf weighted histogram matching is performed to integrate the statistical information of the database. The results show that the proposed highly efficient approach achieves comparable performance with the state-of-the-art for mobile visual search, while the descriptor extraction complexity is largely reduced.