{"title":"基于SVM的人行道除雪机行人检测系统","authors":"Yuta Sasaki, T. Emaru, Ankit A. Ravankar","doi":"10.1109/IEEECONF49454.2021.9382618","DOIUrl":null,"url":null,"abstract":"In this paper, we present a novel pedestrian detection system for sidewalk snow removing vehicles particularly for night driving scenarios. The information in front of the snowplow is obtained by clustering and classifying objects using LiDAR point clouds. A robust pedestrian detection and classification algorithm using the support vector machine(SVM) is proposed. We tested the system on an actual machine and the accuracy our method is verified by experiments.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"SVM based Pedestrian Detection System for Sidewalk Snow Removing Machines\",\"authors\":\"Yuta Sasaki, T. Emaru, Ankit A. Ravankar\",\"doi\":\"10.1109/IEEECONF49454.2021.9382618\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a novel pedestrian detection system for sidewalk snow removing vehicles particularly for night driving scenarios. The information in front of the snowplow is obtained by clustering and classifying objects using LiDAR point clouds. A robust pedestrian detection and classification algorithm using the support vector machine(SVM) is proposed. We tested the system on an actual machine and the accuracy our method is verified by experiments.\",\"PeriodicalId\":395378,\"journal\":{\"name\":\"2021 IEEE/SICE International Symposium on System Integration (SII)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE/SICE International Symposium on System Integration (SII)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEECONF49454.2021.9382618\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/SICE International Symposium on System Integration (SII)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEECONF49454.2021.9382618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SVM based Pedestrian Detection System for Sidewalk Snow Removing Machines
In this paper, we present a novel pedestrian detection system for sidewalk snow removing vehicles particularly for night driving scenarios. The information in front of the snowplow is obtained by clustering and classifying objects using LiDAR point clouds. A robust pedestrian detection and classification algorithm using the support vector machine(SVM) is proposed. We tested the system on an actual machine and the accuracy our method is verified by experiments.
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