Muhamamd Ishfaq Hussain, Shoaib Azam, Farzeen Munir, Zafran Khan, M. Jeon
{"title":"Multiple Objects Tracking using Radar for Autonomous Driving","authors":"Muhamamd Ishfaq Hussain, Shoaib Azam, Farzeen Munir, Zafran Khan, M. Jeon","doi":"10.1109/IEMTRONICS51293.2020.9216363","DOIUrl":null,"url":null,"abstract":"Object detection and tracking are the integral elements for the perception of the spatio-temporal environment. The availability and affordability of camera and lidar as the leading sensor modalities have used for object detection and tracking in research. The usage of deep learning algorithms for the object detection and tracking using camera and lidar have illustrated the promising results, but these sensor modalities are prone to weather conditions, have sparse data and spatial resolution problems. In this work, we explore the problem of detecting distant objects and tracking using radar. For the efficacy of our proposed work, extensive experimentation in different traffic scenario are performed by using our self-driving car test-bed.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Object detection and tracking are the integral elements for the perception of the spatio-temporal environment. The availability and affordability of camera and lidar as the leading sensor modalities have used for object detection and tracking in research. The usage of deep learning algorithms for the object detection and tracking using camera and lidar have illustrated the promising results, but these sensor modalities are prone to weather conditions, have sparse data and spatial resolution problems. In this work, we explore the problem of detecting distant objects and tracking using radar. For the efficacy of our proposed work, extensive experimentation in different traffic scenario are performed by using our self-driving car test-bed.