{"title":"基于密集立体的道路障碍物检测实时ROI生成","authors":"Soon Kwon, Hyuk-Jae Lee","doi":"10.1109/ISOCC.2016.7799840","DOIUrl":null,"url":null,"abstract":"The use of 3D visual information has become widespread as an essential cue for detecting on-road obstacles in ADAS. In this paper, we propose an accurate dense-stereo-based system for the generation of on-road obstacle ROIs. To balance the concerns of computation overhead and algorithm accuracy, this paper presents an efficient depth map generation that combines global stereo matching with depth up-sampling. The entire system has been implemented with a hardware and software partitioning method running on an FPGA and embedded CPU for real-time processing. The implementation results verify that the proposed stereo vision system efficiently outputs accurate ROI candidates for on-road obstacle detection.","PeriodicalId":278207,"journal":{"name":"2016 International SoC Design Conference (ISOCC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Dense stereo-based real-time ROI generation for on-road obstacle detection\",\"authors\":\"Soon Kwon, Hyuk-Jae Lee\",\"doi\":\"10.1109/ISOCC.2016.7799840\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of 3D visual information has become widespread as an essential cue for detecting on-road obstacles in ADAS. In this paper, we propose an accurate dense-stereo-based system for the generation of on-road obstacle ROIs. To balance the concerns of computation overhead and algorithm accuracy, this paper presents an efficient depth map generation that combines global stereo matching with depth up-sampling. The entire system has been implemented with a hardware and software partitioning method running on an FPGA and embedded CPU for real-time processing. The implementation results verify that the proposed stereo vision system efficiently outputs accurate ROI candidates for on-road obstacle detection.\",\"PeriodicalId\":278207,\"journal\":{\"name\":\"2016 International SoC Design Conference (ISOCC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International SoC Design Conference (ISOCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISOCC.2016.7799840\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International SoC Design Conference (ISOCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISOCC.2016.7799840","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dense stereo-based real-time ROI generation for on-road obstacle detection
The use of 3D visual information has become widespread as an essential cue for detecting on-road obstacles in ADAS. In this paper, we propose an accurate dense-stereo-based system for the generation of on-road obstacle ROIs. To balance the concerns of computation overhead and algorithm accuracy, this paper presents an efficient depth map generation that combines global stereo matching with depth up-sampling. The entire system has been implemented with a hardware and software partitioning method running on an FPGA and embedded CPU for real-time processing. The implementation results verify that the proposed stereo vision system efficiently outputs accurate ROI candidates for on-road obstacle detection.
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