Abnormal acoustic event localization based on selective frequency bin in high noise environment for audio surveillance

In this paper, a method for source localization for surveillance system is presented. In particular, we propose an algorithm for abnormal acoustic event localization based on a novel approach of relevant frequency bin selections by statistical analyses. By means of selective frequency bin, it becomes possible to localize the event more accurately in high noise environment with low computational complexity. The effectiveness is verified through the experimental results in varied noise environments with different levels of Signal to Noise Ratio (SNR).