Clothing-to-words mapping using word separation method

With the development of E-commerce, clothing search on Internet emerges to be a valuable and challenging problem. Compared with the standard image retrieval approach, there are two main difficulties in clothing search. The first is the numerous clothing variation. Another is that people like to search the clothing, which have the same visual elements under the numerous variation. Motivated by Graph Cut method, an approach called word separation method is proposed to map the clothing visual elements to words, which can simultaneously take into account the image-to-image relationship, the image-to-word relationship and the word-to-word relationship. In our work, the meaningful words from web pages are represented by the graph nodes. The graph edges are weighted by the context of data set, which is from Internet. The experimental results on the clothing data set demonstrate the efficiency, effectiveness and robustness of our method.

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► The visual elements of clothing images are mapped to words by the domain knowledge by using graph-cut like method.
► We analyze the size of clothing domain knowledge in different clothing categories.
► Thorough comparisons and experiments with different image features on clothing search are provided.