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Video summarization is a timely and rapidly developing research field with broad commercial interest, due to the increasing availability of massive video data. Relevant algorithms face the challenge of needing to achieve a careful balance between summary compactness, enjoyability, and content coverage. The specific case of stereoscopic 3D theatrical films has become more important over the past years,...
A novel, low-level video frame description method is proposed that is able to compactly capture informative image statistics from luminance, color and stereoscopic disparity video data, both in a global and in various local scales. Thus, scene texture, illumination and geometry properties may succinctly be contained within a single frame feature descriptor, which can subsequently be employed as a...
In this paper, we propose a method for video summarization based on human activity description. We formulate this problem as the one of automatic video segment selection based on a learning process that employs salient video segment paradigms. For this one-class classification problem, we introduce a novel variant of the One-Class Support Vector Machine (OC-SVM) classifier that exploits subclass information...
A novel method for image authentication and tamper proofing is proposed. A binary watermark is embedded in a grayscale or a color host image. The method succeeds in detecting alterations made in a watermarked image. The proposed method is robust against high quality lossy image compression. It provides the user not only with a measure for the authenticity of the test image but also with an image map...
In this paper, we describe a method for video summarization that operates on a video segment level. We formulate this problem as the one of automatic video segment selection based on a learning process that employs salient video segment paradigms. We design an hierarchical learning scheme that consists of two steps. At the first step, an unsupervised process is performed in order to determine salient...
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