{"title":"使用时空纹理图像对距离和运动进行定性估计","authors":"Zhigang Zhu, Guangyou Xu, Dingji Shi","doi":"10.1109/ICPR.1994.576425","DOIUrl":null,"url":null,"abstract":"In this paper we model the problem of structure from motion as the range estimation with known motion. First, we approximate the motion within a reasonable time interval as a 3D translation and thus some image transformations are applied to convert an arbitrary motion to a 1D translation. Then we analyse the epipolar plane image in the Fourier domain to avoid the feature extraction and correspondence problems. Experimental results with real scene images have shown the efficiency and robustness of the approach.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Qualitative estimations of range and motion using spatio-temporal textural images\",\"authors\":\"Zhigang Zhu, Guangyou Xu, Dingji Shi\",\"doi\":\"10.1109/ICPR.1994.576425\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we model the problem of structure from motion as the range estimation with known motion. First, we approximate the motion within a reasonable time interval as a 3D translation and thus some image transformations are applied to convert an arbitrary motion to a 1D translation. Then we analyse the epipolar plane image in the Fourier domain to avoid the feature extraction and correspondence problems. Experimental results with real scene images have shown the efficiency and robustness of the approach.\",\"PeriodicalId\":312019,\"journal\":{\"name\":\"Proceedings of 12th International Conference on Pattern Recognition\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 12th International Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.1994.576425\",\"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 of 12th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.1994.576425","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Qualitative estimations of range and motion using spatio-temporal textural images
In this paper we model the problem of structure from motion as the range estimation with known motion. First, we approximate the motion within a reasonable time interval as a 3D translation and thus some image transformations are applied to convert an arbitrary motion to a 1D translation. Then we analyse the epipolar plane image in the Fourier domain to avoid the feature extraction and correspondence problems. Experimental results with real scene images have shown the efficiency and robustness of the approach.