Acoustic Based Surveillance System for Intrusion Detection

This paper describes a surveillance system for intrusion detection which is based only on information derived from the processing of audio signals acquired by a Distributed Microphone Network (DMN). In particular the system exploits different acoustic features and estimates of acoustic event positions in order to detect intrusion and reject possible false alarms that may be generated by sound sources inside and outside the monitored room. An evaluation has been conducted in order to measure the performance in terms of false alarms and missed alarms in presence of acoustic events produced inside and outside a test room.The obtained results are very promising and encouraging for future works aimed at improving the actual system accuracy.