{"title":"从图像序列递归深度估计","authors":"S. Vasikarla, M. Hanmandlu","doi":"10.1109/ITCC.2000.844211","DOIUrl":null,"url":null,"abstract":"This paper gives the theoretical framework for recursively estimating the depth and motion parameters from the image motion equation derived using the spherical projection. An extended Kalman filter is employed for estimation. Results have been found to be encouraging in some cases when applied on two case studies involving vase and cube respectively.","PeriodicalId":146581,"journal":{"name":"Proceedings International Conference on Information Technology: Coding and Computing (Cat. No.PR00540)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Recursive depth estimation from a sequence of images\",\"authors\":\"S. Vasikarla, M. Hanmandlu\",\"doi\":\"10.1109/ITCC.2000.844211\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper gives the theoretical framework for recursively estimating the depth and motion parameters from the image motion equation derived using the spherical projection. An extended Kalman filter is employed for estimation. Results have been found to be encouraging in some cases when applied on two case studies involving vase and cube respectively.\",\"PeriodicalId\":146581,\"journal\":{\"name\":\"Proceedings International Conference on Information Technology: Coding and Computing (Cat. No.PR00540)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings International Conference on Information Technology: Coding and Computing (Cat. No.PR00540)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITCC.2000.844211\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings International Conference on Information Technology: Coding and Computing (Cat. No.PR00540)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITCC.2000.844211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recursive depth estimation from a sequence of images
This paper gives the theoretical framework for recursively estimating the depth and motion parameters from the image motion equation derived using the spherical projection. An extended Kalman filter is employed for estimation. Results have been found to be encouraging in some cases when applied on two case studies involving vase and cube respectively.