F. Nowruzi, Dhanvin Kolhatkar, Prince Kapoor, Fahed Al Hassanat, E. J. Heravi, R. Laganière, Julien Rebut, Waqas Malik
{"title":"基于汽车雷达的深度开放空间分割","authors":"F. Nowruzi, Dhanvin Kolhatkar, Prince Kapoor, Fahed Al Hassanat, E. J. Heravi, R. Laganière, Julien Rebut, Waqas Malik","doi":"10.1109/ICMIM48759.2020.9299052","DOIUrl":null,"url":null,"abstract":"In this work, we propose the use of radar with advanced deep segmentation models to identify open space in parking scenarios. A publically available dataset of radar observations called SCORP was collected. Deep models are evaluated with various radar input representations. Our proposed approach achieves low memory usage and real-time processing speeds, and is thus very well suited for embedded deployment.","PeriodicalId":150515,"journal":{"name":"2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Deep Open Space Segmentation using Automotive Radar\",\"authors\":\"F. Nowruzi, Dhanvin Kolhatkar, Prince Kapoor, Fahed Al Hassanat, E. J. Heravi, R. Laganière, Julien Rebut, Waqas Malik\",\"doi\":\"10.1109/ICMIM48759.2020.9299052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we propose the use of radar with advanced deep segmentation models to identify open space in parking scenarios. A publically available dataset of radar observations called SCORP was collected. Deep models are evaluated with various radar input representations. Our proposed approach achieves low memory usage and real-time processing speeds, and is thus very well suited for embedded deployment.\",\"PeriodicalId\":150515,\"journal\":{\"name\":\"2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMIM48759.2020.9299052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMIM48759.2020.9299052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Deep Open Space Segmentation using Automotive Radar
In this work, we propose the use of radar with advanced deep segmentation models to identify open space in parking scenarios. A publically available dataset of radar observations called SCORP was collected. Deep models are evaluated with various radar input representations. Our proposed approach achieves low memory usage and real-time processing speeds, and is thus very well suited for embedded deployment.