Talha Karadeniz

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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 novel approach, which is based on combining the competence of interest point detectors to capture primitives and the capability of geometric constraints to discriminate between spatial configurations of these primitives is presented. In the proposed approach, the geometric constraints are enforced by means of barycentric coordinates, a mathematical tool(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)
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 work, we aimed to demonstrate that covariance estimation methods can be used for trajectory classification. We have shown that, features obtained via shrunk covariance estimation are suitable for describing trajectories. We have arrived to the conclusion that, when compared to Dynamic Time Warping, the explained technique is faster and may yield(More)
Concept detection stands as an important problem for many applications like efficient indexing and retrieval in large video archives. In this work, for detection of diverse and distinct concepts a concept detection system (KavTan) that combines a variety of information sources under a single structure is proposed. The proposed system consists of Generalized(More)
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