{"title":"基于斜率趋势的消失点检测全向视觉机器人定位","authors":"Jun-Yu Yang, Feng‐Li Lian","doi":"10.1109/ICMA.2013.6618062","DOIUrl":null,"url":null,"abstract":"This paper proposes one novel method to detect vanishing points in indoor environment. The original environmental data are from a standard omnidirectional camera equipped on one mobile robot. The orientation information in the panoramic image captured by the omnidirectional camera is computed by any standard edge detection, and further analyzed by the proposed slope trend approach. Related experimental studies in different scenarios are performed to demonstrate the feasibility of the approach.","PeriodicalId":335884,"journal":{"name":"2013 IEEE International Conference on Mechatronics and Automation","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vanishing point detection based on slope trend for omnidirectional vision-based robot localization\",\"authors\":\"Jun-Yu Yang, Feng‐Li Lian\",\"doi\":\"10.1109/ICMA.2013.6618062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes one novel method to detect vanishing points in indoor environment. The original environmental data are from a standard omnidirectional camera equipped on one mobile robot. The orientation information in the panoramic image captured by the omnidirectional camera is computed by any standard edge detection, and further analyzed by the proposed slope trend approach. Related experimental studies in different scenarios are performed to demonstrate the feasibility of the approach.\",\"PeriodicalId\":335884,\"journal\":{\"name\":\"2013 IEEE International Conference on Mechatronics and Automation\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Mechatronics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA.2013.6618062\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Mechatronics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2013.6618062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vanishing point detection based on slope trend for omnidirectional vision-based robot localization
This paper proposes one novel method to detect vanishing points in indoor environment. The original environmental data are from a standard omnidirectional camera equipped on one mobile robot. The orientation information in the panoramic image captured by the omnidirectional camera is computed by any standard edge detection, and further analyzed by the proposed slope trend approach. Related experimental studies in different scenarios are performed to demonstrate the feasibility of the approach.