Medeni Soysal

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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)
This article introduces a novel method for 3D object recognition, which utilizes well-known local features in a more efficient way, without any reliance on partial or global planarity. Geometrically consistent local features, which form the crucial basis for object recognition, are identified using affine 3D geometric invariants. The utilization of 3D(More)
Immense increase in the number of multimedia content accessible from television and internet with the help developing technologies reveals efficient supervision and classification of such content as a problem. Relevance feedback is a technique which relies on evaluation of retrieval results by humans and enables reduce the semantic gap between ideas and low(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)
As a recent trend some TV stations prefer to use animated logos, therefore the detection of the presence of an animated TV logo emerges as a new requirement for certain applications. In this paper we present a novel method for the detection of animated television logos in real-time. The main idea is to handle all frames of the animated logo in a unified(More)