The paper presents a knowledge-based system designed to detect evidence of aggression by means of audio analysis. The detection is based on the way sounds are analyzed and how they attract attention in the human auditory system. The performance achieved is comparable to human performance in complex social environments. The SIgard system has been deployed in a number of different real-life situations and was tested extensively in the inner city of Groningen. Experienced police observers have annotated ～1400 recordings with various degrees of shouting, which were used for optimization. All essential events and a small number of nonessential aggressive events were detected. The system produces only a few false alarms (non-shouts) per microphone per year and misses no incidents. This makes it the first successful detection system for a non-trivial target in an unconstrained environment.
展开▼
