{"title":"Modification of DBSCAN and application to range/Doppler/DoA measurements for pedestrian recognition with an automotive radar system","authors":"T. Wagner, R. Feger, A. Stelzer","doi":"10.1109/EURAD.2015.7346289","DOIUrl":null,"url":null,"abstract":"We present in this paper modifications of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm in order to detect pedestrians with a conventional automotive 77-GHz frequency modulated radar system. These modification include dimension scaling as preprocessing and a generalization of the ε-neighborhood notation by introducing a size parameter to constitute the new Ellipsoid DBSCAN (EDBSCAN) algorithm. With these modifications we could successfully cluster real-world measurement data in order to get reasonable cluster representations of pedestrians in a cluttered environment.","PeriodicalId":376019,"journal":{"name":"2015 European Radar Conference (EuRAD)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 European Radar Conference (EuRAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURAD.2015.7346289","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 36
Abstract
We present in this paper modifications of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm in order to detect pedestrians with a conventional automotive 77-GHz frequency modulated radar system. These modification include dimension scaling as preprocessing and a generalization of the ε-neighborhood notation by introducing a size parameter to constitute the new Ellipsoid DBSCAN (EDBSCAN) algorithm. With these modifications we could successfully cluster real-world measurement data in order to get reasonable cluster representations of pedestrians in a cluttered environment.
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