BEHAVIOUR RECOGNITION AND EXPLANATION FOR VIDEO SURVEILLANCE

摘要

This paper is concerned with producing high-level reports and explanations of human activity in video from a single, static camera. The scenarios we focus on are urban surveillance and sports video where the imaged person is medium/low resolution. The final output is text descriptions which not only describe, in human-readable terms, what is happening but also explain the interactions which take place. The input to the reasoning process is the information obtained from lower-level algorithms which provide an abstraction from the image data to qualitative descriptions of human activity. Causal explanations of global scene activity, particularly where interesting events have occurred, is achieved using an extensible, rule-based method. The complete system represents a general technique for video understanding.