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Measuring image similarity is a central topic in computer vision. In this paper, we learn similarity from Flickr groups and use it to organize photos. Two images are similar if they are likely to belong to the same Flickr groups. Our approach is enabled by a fast Stochastic Intersection Kernel MAchine (SIKMA) training algorithm, which we propose. This proposed training method will be useful for many...
Automatic semantic scene classification is a challenging research topic in computer vision and it is also a promising solution to scene understanding and image semantic retrieval. In this paper, novel techniques are proposed to implement multi-semantic scene classification. We first extract some regions of interest (ROIs) from each image based on image-driven, bottom-up visual attention model, and...
Object recognition systems designed for Internet applications typically need to adapt to userspsila needs in a flexible fashion and scale up to very large data sets. In this paper, we analyze the complexity of several multiclass SVM-based algorithms and highlight the computational bottleneck they suffer at test time: comparing the input image to every training image. We propose an algorithm that overcomes...
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