Acoustic Based Surveillance System for Intrusion Detection
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
An adaptive framework for acoustic monitoring of potential hazards
EURASIP Journal on Audio, Speech, and Music Processing
FollowMe: enhancing mobile applications with open infrastructure sensing
Proceedings of the 12th Workshop on Mobile Computing Systems and Applications
Multimedia Tools and Applications
2D space---time wave-digital multi-fan filter banks for signals consisting of multiple plane waves
Multidimensional Systems and Signal Processing
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This paper describes an audio-based video surveillance system which automatically detects anomalous audio events in a public square, such as screams or gunshots, and localizes the position of the acoustic source, in such a way that a video-camera is steered consequently. The system employs two parallel GMM classifiers for discriminating screams from noise and gunshots from noise, respectively. Each classifier is trained using different features, chosen from a set of both conventional and innovative audio features. The location of the acoustic source which has produced the sound event is estimated by computing the time difference of arrivals of the signal at a microphone array and using linear-correction least square localization algorithm. Experimental results show that our system can detect events with a precision of 93% at a false rejection rate of 5% when the SNR is 10dB, while the source direction can be estimated with a precision of one degree. A real-time implementation of the system is going to be installed in a public square of Milan.