Multimodal concept detection on multimedia data- RTUK SKAAS KavTan system

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 Audio Concept Detection and Audio Keyword Detection sub-modules that use audio data and Generalized Visual Concept Detection, Video Text Detection, Human Detection, Nudity Detection, Blood Detection, Flag Detection and Skin Detection sub-modules that use visual data. Each concept is detected by using one or more of the mentioned modules. Proposed concept detection system is tested against multiple concepts and system performance is reported. It is observed that for most of the concepts high performance can be achieved with this approach.