Real-time content-based access to live video data requires content analysis applications that are able to process the video data at least as fast as the video data is made available to the application and with an acceptable error rate. Statements as this express quality of service (QoS) requirements to the application. In order to provide some level of control of the QoS provided, the video content analysis application must be scalable and resource aware so that requirements of timeliness and accuracy can be met by allocating additional processing resources. In this paper we present a general architecture of video content analysis applications including a model for specifying requirements of timeliness and accuracy. The salient features of the architecture include its combination of probabilistic knowledge-based media content analysis with QoS and distributed resource management to handle QoS requirements, and its independent scalability at multiple logical levels of distribution. We ...
Viktor S. Wold Eide, Frank Eliassen, Ole-Christoff