Object-based and Event-based Semantic Video Adaptation

Semantic video adaptation allows to transmit video contentwith different viewing quality, depending on the relevanceof the content from the user’s viewpoint. To this end, an automatic annotation subsystem must be employed thatautomatically detect relevant objects and events in the videostream. In this paper we present a composite framework thatis made of an automatic annotation engine and a semantics-based adaptation module. Three new different compression solutions are proposed that work at the object or event level. Their performance is compared according to a new measure that takes into account the user’s satisfaction and the effects on it of the errors in the annotation module.