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We propose a novel framework for visual saliency detection based on a simple principle: images sharing their global visual appearances are likely to share similar salience. Assuming that an annotated image database is available, we first retrieve the most similar images to the target image; secondly, we build a simple classifier and we use it to generate saliency maps. Finally, we refine the maps...
A face recognition algorithm based on a iterated k-means classification technique will be presented in this paper. The proposed algorithm, when compared with popular PCA algorithms for face recognition has an improved recognition rate on various benchmark datasets. The presented algorithm, unlike PCA, is not a dimensional reduction algorithm, nonetheless it yields barycentric-faces which can be used...
We propose a methodology to analyze and visualize the relationships and influences between painters. We build a graph where each painter is a node and an edge between two nodes is weighted by the painters' similarity. The similarity of two painters is measured as a function of the similarity between their paintings. Although the image representation we use was initially developed for the detection...
In a computational context, classification refers to assigning objects to different classes with respect to their features, which can be mapped to qualitative or quantitative variables. Several techniques have been developed recently to map the available information into a set of features (feature space) that improve the classification performance. Kernel functions provide a nonlinear mapping that...
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