{"title":"Depth from Defocus applied to Auto Focus","authors":"Shunsuke Yasugi, Khang Nguyen, Kozo Ezawa, Takashi Kawamura","doi":"10.1109/GCCE.2014.7031237","DOIUrl":null,"url":null,"abstract":"Depth from Defocus (DFD) is known as the technology which is able to estimate depth in the scene by a monocular camera without any additive devices. Using this advantage of DFD, we improved the speed of Auto Focus (AF). To apply DFD to AF, it is necessary to capture 2 images that have a small amount of “difference in focal positions” (we call DiFP). In this paper, we show the performance of the depth estimation when the DiFP is changed, and verify that Low Pass Filter is a good solution to get robust depth.","PeriodicalId":145771,"journal":{"name":"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCCE.2014.7031237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Depth from Defocus (DFD) is known as the technology which is able to estimate depth in the scene by a monocular camera without any additive devices. Using this advantage of DFD, we improved the speed of Auto Focus (AF). To apply DFD to AF, it is necessary to capture 2 images that have a small amount of “difference in focal positions” (we call DiFP). In this paper, we show the performance of the depth estimation when the DiFP is changed, and verify that Low Pass Filter is a good solution to get robust depth.
散焦深度(Depth from Defocus, DFD)是一种无需任何附加设备就能通过单目相机估算场景深度的技术。利用DFD的这个优势,我们提高了自动对焦(AF)的速度。为了将DFD应用于自动对焦,有必要捕获2张有少量“焦位差异”的图像(我们称之为DiFP)。在本文中,我们展示了当DiFP改变时深度估计的性能,并验证了低通滤波器是获得鲁棒深度的良好解决方案。