{"title":"Rolling-Shutter-Aware Differential SfM and Image Rectification","authors":"Bingbing Zhuang, L. Cheong, Gim Hee Lee","doi":"10.1109/ICCV.2017.108","DOIUrl":null,"url":null,"abstract":"In this paper, we develop a modified differential Structure from Motion (SfM) algorithm that can estimate relative pose from two consecutive frames despite of Rolling Shutter (RS) artifacts. In particular, we show that under constant velocity assumption, the errors induced by the rolling shutter effect can be easily rectified by a linear scaling operation on each optical flow. We further propose a 9-point algorithm to recover the relative pose of a rolling shutter camera that undergoes constant acceleration motion. We demonstrate that the dense depth maps recovered from the relative pose of the RS camera can be used in a RS-aware warping for image rectification to recover high-quality Global Shutter (GS) images. Experiments on both synthetic and real RS images show that our RS-aware differential SfM algorithm produces more accurate results on relative pose estimation and 3D reconstruction from images distorted by RS effect compared to standard SfM algorithms that assume a GS camera model. We also demonstrate that our RS-aware warping for image rectification method outperforms state-of-the-art commercial software products, i.e. Adobe After Effects and Apple Imovie, at removing RS artifacts.","PeriodicalId":6559,"journal":{"name":"2017 IEEE International Conference on Computer Vision (ICCV)","volume":"46 1","pages":"948-956"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"57","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Computer Vision (ICCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2017.108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 57
Abstract
In this paper, we develop a modified differential Structure from Motion (SfM) algorithm that can estimate relative pose from two consecutive frames despite of Rolling Shutter (RS) artifacts. In particular, we show that under constant velocity assumption, the errors induced by the rolling shutter effect can be easily rectified by a linear scaling operation on each optical flow. We further propose a 9-point algorithm to recover the relative pose of a rolling shutter camera that undergoes constant acceleration motion. We demonstrate that the dense depth maps recovered from the relative pose of the RS camera can be used in a RS-aware warping for image rectification to recover high-quality Global Shutter (GS) images. Experiments on both synthetic and real RS images show that our RS-aware differential SfM algorithm produces more accurate results on relative pose estimation and 3D reconstruction from images distorted by RS effect compared to standard SfM algorithms that assume a GS camera model. We also demonstrate that our RS-aware warping for image rectification method outperforms state-of-the-art commercial software products, i.e. Adobe After Effects and Apple Imovie, at removing RS artifacts.
在本文中,我们开发了一种改进的运动微分结构(SfM)算法,该算法可以在滚动快门(RS)伪影的情况下从两个连续帧中估计相对姿态。特别是,我们证明了在恒定速度假设下,滚动快门效应引起的误差可以很容易地通过对每个光流进行线性缩放操作来纠正。我们进一步提出了一种9点算法来恢复恒定加速度运动下卷帘式相机的相对姿态。我们证明了从RS相机的相对姿态恢复的密集深度图可以用于RS感知的图像校正,以恢复高质量的全局快门(GS)图像。在合成和真实RS图像上的实验表明,与假设GS相机模型的标准SfM算法相比,我们的RS感知差分SfM算法在被RS影响的图像的相对姿态估计和3D重建方面产生了更准确的结果。我们还证明,我们的图像校正方法的RS感知翘曲优于最先进的商业软件产品,即Adobe After Effects和Apple Imovie,在去除RS伪影。