Mashar Tekin

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Concept detection stands as an important problem for efficient indexing and retrieval in large video archives. In this work, the KavTan System, which performs high-level semantic classification in one of the largest TV archives of Turkey, is presented. In this system, concept detection is performed using generalized visual and audio concept detection(More)
A method for adult content classification and nudity detection is presented. Objective of this method is to classify images into different classes, varying on the degree of adult content. We utilize MPEG-7 descriptors to represent visual information. Skin regions are detected to model adult content more precisely, as well as to eliminate false-positives.(More)
Mainline approaches for content description for copy detection utilize global or local descriptors from video and comparing these descriptors for similarity. In the literature [16], it has been shown that local features perform better in terms of robustness on the other hand global features are computationally simpler. Local features for content description(More)
In this notebook paper, we discuss and give an overview of our participation to the High-Level Feature Extraction (HLFE) and Content-Based Copy Detection (CBCD) tasks of TRECVID 2009. In our HLFE system both visual and audio concept detection has been implemented and also complimentary standalone detectors have been incorporated to the system. For the(More)
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