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In this chapter, we present retrieval techniques using content-based and concept-based technologies, for digital image and video database applications. We first deal with the state-of-the-art methods in a content-based framework including: Laplacian mixture model for content characterization, nonlinear relevance feedback, combining audio and visual features for video retrieval, and designing automatic...
This paper studies a support vector machine (SVM) to obtain a decision fusion algorithm for detection of semantic concepts in videos, and its application to films database. Given a movie clip, its spatio-temporal information is captured by audiovisual features. These are then independently inputted to the corresponding matching experts whose outputs are fused at the decision stage by the SVM classifier...
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