{"title":"基于变分法的不同分辨率图像间光流估计","authors":"Rui Zhao, Ruiqin Xiong, Shuyuan Zhu, B. Zeng, Tiejun Huang, Wen Gao","doi":"10.1109/VCIP49819.2020.9301771","DOIUrl":null,"url":null,"abstract":"Traditional optical flow estimation methods mostly focus on images of the same resolution. However, there are some situations requiring optical flow between images of different resolutions, where the traditional approaches suffer from the inequality of spectrum aliasing level. In this paper, we propose a method estimating the flow fields between a clear image and a highly undersampled one. The proposed method simultaneously describes the motion and integral relationship between the images via an integral form image under the assumption of brightness and gradient consistency as well as motion smoothness. We also derive the numerical solution briefly, through which we can solve the equations easily via linearizations. Experimental results on Middlebury and MPI-Sintel datasets demonstrate that our proposed method outperforms traditional methods preprocessing images of different resolutions to be the same size, offering more accurate results.","PeriodicalId":431880,"journal":{"name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optical Flow Estimation Between Images of Different Resolutions via Variational Method\",\"authors\":\"Rui Zhao, Ruiqin Xiong, Shuyuan Zhu, B. Zeng, Tiejun Huang, Wen Gao\",\"doi\":\"10.1109/VCIP49819.2020.9301771\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional optical flow estimation methods mostly focus on images of the same resolution. However, there are some situations requiring optical flow between images of different resolutions, where the traditional approaches suffer from the inequality of spectrum aliasing level. In this paper, we propose a method estimating the flow fields between a clear image and a highly undersampled one. The proposed method simultaneously describes the motion and integral relationship between the images via an integral form image under the assumption of brightness and gradient consistency as well as motion smoothness. We also derive the numerical solution briefly, through which we can solve the equations easily via linearizations. Experimental results on Middlebury and MPI-Sintel datasets demonstrate that our proposed method outperforms traditional methods preprocessing images of different resolutions to be the same size, offering more accurate results.\",\"PeriodicalId\":431880,\"journal\":{\"name\":\"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VCIP49819.2020.9301771\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP49819.2020.9301771","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optical Flow Estimation Between Images of Different Resolutions via Variational Method
Traditional optical flow estimation methods mostly focus on images of the same resolution. However, there are some situations requiring optical flow between images of different resolutions, where the traditional approaches suffer from the inequality of spectrum aliasing level. In this paper, we propose a method estimating the flow fields between a clear image and a highly undersampled one. The proposed method simultaneously describes the motion and integral relationship between the images via an integral form image under the assumption of brightness and gradient consistency as well as motion smoothness. We also derive the numerical solution briefly, through which we can solve the equations easily via linearizations. Experimental results on Middlebury and MPI-Sintel datasets demonstrate that our proposed method outperforms traditional methods preprocessing images of different resolutions to be the same size, offering more accurate results.