{"title":"基于稀疏边缘的视差图的快速障碍物检测","authors":"Dexmont Alejandro Peãa Carrillo, Alistair Sutherland","doi":"10.1109/3DV.2016.80","DOIUrl":null,"url":null,"abstract":"This paper presents a fast approach for computing image stixels from a sparse edge-based disparity map. The use of edge-based disparity maps speeds up the computation of the stixels as only a few pixels must be processed compared to approaches which use dense disparity maps. The proposed approach produces as output the stixels in one of the views of the stereo-pair and a segmentation of the edge-points into obstacle. Additionally the proposed approach allows the identification of partially occluded objects by allowing more than one stixel per image column. The proposed approach is fast to compute with no loss on accuracy.","PeriodicalId":425304,"journal":{"name":"2016 Fourth International Conference on 3D Vision (3DV)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Fast Obstacle Detection Using Sparse Edge-Based Disparity Maps\",\"authors\":\"Dexmont Alejandro Peãa Carrillo, Alistair Sutherland\",\"doi\":\"10.1109/3DV.2016.80\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a fast approach for computing image stixels from a sparse edge-based disparity map. The use of edge-based disparity maps speeds up the computation of the stixels as only a few pixels must be processed compared to approaches which use dense disparity maps. The proposed approach produces as output the stixels in one of the views of the stereo-pair and a segmentation of the edge-points into obstacle. Additionally the proposed approach allows the identification of partially occluded objects by allowing more than one stixel per image column. The proposed approach is fast to compute with no loss on accuracy.\",\"PeriodicalId\":425304,\"journal\":{\"name\":\"2016 Fourth International Conference on 3D Vision (3DV)\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Fourth International Conference on 3D Vision (3DV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/3DV.2016.80\",\"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 Fourth International Conference on 3D Vision (3DV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3DV.2016.80","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast Obstacle Detection Using Sparse Edge-Based Disparity Maps
This paper presents a fast approach for computing image stixels from a sparse edge-based disparity map. The use of edge-based disparity maps speeds up the computation of the stixels as only a few pixels must be processed compared to approaches which use dense disparity maps. The proposed approach produces as output the stixels in one of the views of the stereo-pair and a segmentation of the edge-points into obstacle. Additionally the proposed approach allows the identification of partially occluded objects by allowing more than one stixel per image column. The proposed approach is fast to compute with no loss on accuracy.