ACOUSTIC SURVEILLANCE BASED ON HIGHER-ORDER LOCAL AUTO-CORRELATION

被引：0
|
作者：
Sasou, Akira [1 ]
机构：
[1] Natl Inst Adv Ind Sci & Technol, AIST, Tsukuba, Ibaraki, Japan
来源：
2011 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP) | 2011年
关键词：
HLAC; acoustic surveillance; Cepstrum;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The importance of video-surveillance applications has been increasing with the increase of crime and terrorism. In addition to traditional video cameras, the use of acoustic sensors in surveillance and monitoring applications is also becoming increasingly important. In this paper, we apply a High-order Local Auto-Correlation (HLAC) system, which has succeeded in video surveillance application, to extract features from acoustic signals for acoustic-surveillance systems. Experiment results confirmed that the proposed acoustic-surveillance system outperforms a cepstrum-based one under all SNR conditions.
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页数：5
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