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One of the simpler and most used method to alter the content of a digital image is to copy-move a portion of it onto another area with the intent, usually, to hide something awkward. In image forensics scientific community, this kind of modification is generally detected by resorting at techniques based on SIFT features that provide a local description which is robust to global geometric transformations...
In this paper we propose a new method for human action categorization by using an effective combination of a new 3D gradient descriptor with an optic flow descriptor, to represent spatio-temporal interest points. These points are used to represent video sequences using a bag of spatio-temporal visual words, following the successful results achieved in object and scene classification. We extensively...
Action recognition is a crucial task to provide high-level semantic description of the video content, particularly in the case of sports videos. The bag-of-words (BoW) approach has proven to be successful for the categorization of objects and scenes in images, but it's unable to model temporal information between consecutive frames for video event recognition. In this paper, we present an approach...
In this work is presented a novel approach for the classification of audio concepts in broadcast soccer videos using deep belief network (DBN), a probabilistic neural network with several hidden layers. Comparison with support vector machine (SVM) classifiers has been carried on, showing that our preliminary results are promisingly comparable to the state-of-the-art.
In this paper we describe a system for automatic detection and recognition of trademarks in sports videos. We propose a compact representation of trademarks based on SIFT feature points and a matching algorithm to robustly detect and retrieve trademarks in a variety of different sports video types. Trademark localization is performed through robust clustering of matched feature points in the video...
Recent efforts attempt to combine together information of different passive methods. Critical issues in this research are the choice of data and how to combine such data in order to increase the overall information. The combination of stereo matching and silhouette information has recently received considerable attention both for obtaining high quality 3D models and for modelling 3D dynamic scenes...
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