{"title":"使用Kinect传感器定位不同位置的声源","authors":"Jason Orchard, Yusuke Hioka","doi":"10.1109/SAS.2014.6798932","DOIUrl":null,"url":null,"abstract":"A novel acoustic signal processing algorithm for sound source localisation is proposed and is implemented using two Microsoft Kinect sensors. The proposed method performs sound source localisation using a two stage method. A coarse grain location estimate is first made followed by a more accurate estimate of sound source location by estimating power spectral densities of a number of two-dimensional spatial regions. The paper outlines the sound source localisation method is able to localise a sound source within a series of predefined spatial regions. Testing of the proposed method shows it is able to localise an active sound source whilst maintaining low computational cost and can maintain good localisation performance whilst ambient noise is present.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Localisation of a sound source in different positions using Kinect sensors\",\"authors\":\"Jason Orchard, Yusuke Hioka\",\"doi\":\"10.1109/SAS.2014.6798932\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel acoustic signal processing algorithm for sound source localisation is proposed and is implemented using two Microsoft Kinect sensors. The proposed method performs sound source localisation using a two stage method. A coarse grain location estimate is first made followed by a more accurate estimate of sound source location by estimating power spectral densities of a number of two-dimensional spatial regions. The paper outlines the sound source localisation method is able to localise a sound source within a series of predefined spatial regions. Testing of the proposed method shows it is able to localise an active sound source whilst maintaining low computational cost and can maintain good localisation performance whilst ambient noise is present.\",\"PeriodicalId\":125872,\"journal\":{\"name\":\"2014 IEEE Sensors Applications Symposium (SAS)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Sensors Applications Symposium (SAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAS.2014.6798932\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Sensors Applications Symposium (SAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAS.2014.6798932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Localisation of a sound source in different positions using Kinect sensors
A novel acoustic signal processing algorithm for sound source localisation is proposed and is implemented using two Microsoft Kinect sensors. The proposed method performs sound source localisation using a two stage method. A coarse grain location estimate is first made followed by a more accurate estimate of sound source location by estimating power spectral densities of a number of two-dimensional spatial regions. The paper outlines the sound source localisation method is able to localise a sound source within a series of predefined spatial regions. Testing of the proposed method shows it is able to localise an active sound source whilst maintaining low computational cost and can maintain good localisation performance whilst ambient noise is present.