Resource-adaptive multimedia analysis on stream mining systems

Large-scale multimedia semantic concept detection requires realtime identification of a set of concepts in streaming video or large image datasets. The potentially high data volumes of multimedia content, and high complexity associated with individual concept detectors, have hindered the practical deployment of many current solutions. In this paper, we present a summary of our work in building systems and applications for resource adaptive semantic concept detection in multimedia using large-scale distributed stream mining systems. We construct such concept detection applications as a hierarchical topology of individual concept detectors, and deploy them on distributed processing infrastructure. We then focus on dynamically configuring individual concept detectors to meet system imposed resource constraints while minimizing a penalty defined in terms of the misclassification cost. We present multiple centralized and distributed algorithms for this configuration, and describe the imple...

• Type: Journal
• Year: 2009
• Where: ICMCS
• Authors: Deepak S. Turaga, Rong Yan, Olivier Verscheure, Brian Foo, Fangwen Fu, Hyunggon Park, Mihaela van der Schaar
• Keywords: Concept Detection, ICMCS 2009, Individual Concept Detectors, Multimedia, Semantic Concept Detection