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This paper presents a framework to extract subset which only contains one person's video segments from a superfluous home video set. This is a semantic level multimedia application. We proposed a co-clustering method based on facial and body feature, and defined a new type of measurement to combine the two features more reasonable. 2D-PCA detector is used to extract facial feature, and K-Means algorithm...
In this paper, we adopt the integration model of spatial feature correlations to order the indexing and matching features, and address the computational ineffectiveness and inefficiency of local features based logo detection methods. We propose a Spatial InteGrated Matching Association algorithm (SIGMA) for logo detection in natural scene that contains extremely variances in viewpoints, illuminations...
Matching is a central problem in pattern recognition and computer vision, its applications includes object detection and tracking. HCMA (hierarchical chamfer matching) is a classical image matching algorithm, which utilizes the edge information to match the images robustly and the multi-resolution pyramid to accelerate the matching process. However, for images with cluttered background and high resolution,...
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