The explosive growth of web images not only brings many technical challenges to image search, but also provides almost unlimited training data and new ideas to various computer vision problems.This paper presents a brief historical review of three stages of image retrieval, with a particular emphasis on the impact of large-scale web images to image retrieval.Based on the review, the paper discusses the fundamental problem of feature extraction in image retrieval, and the recent research trend on visual pattern mining to bridge the semantic gap.According to their representation granularity, the paper divides visual patterns into five categories and introduces their related work respectively, which also shows the great importance of big data to visual pattern mining.
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