Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
MM '09 Proceedings of the 17th ACM international conference on Multimedia
iLike: integrating visual and textual features for vertical search
Proceedings of the international conference on Multimedia
iSearch: towards precise retrieval of item image
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
On the Annotation of Web Videos by Efficient Near-Duplicate Search
IEEE Transactions on Multimedia
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Online shopping becomes a convenient way for billions for web users to purchase the products, especially clothes. A large portion of the product images are various types of apparel often including a human model from cluttered and non-uniform natural backgrounds, which makes visual product search a challenging task. In this work, we propose an approach for interactive product image search with complex scenes, which combines the interactive image segmentation for query images, and efficient graph-based principal object extraction for backend image database to extract the foreground objects, respectively. Experiments on a large scale dataset with 1.36 million product images crawled from Taobao demonstrate the effectiveness of the proposed solution.