曼哈顿世界的卷帘门修正

Pulak Purkait, C. Zach, A. Leonardis
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引用次数: 37

摘要

绝大多数消费类相机使用的是卷帘式快门机制,在拍摄图像时,由于行间延迟,通常会产生失真的图像。最近的单眼卷帘门补偿方法利用模糊核、线段直线度以及角度和长度保留。然而,它们没有明确地将场景几何形状合并到滚动快门校正中,因此,关于3D场景几何形状的信息经常在校正过程中被扭曲。在本文中,我们提出了一种新的方法,该方法利用场景的几何特性-特别是消失方向-来估计在滚动快门曝光期间从单个扭曲图像中的相机运动。该方法联合估计正交消失方向和滚动快门相机运动。我们在合成和真实数据集上进行了广泛的实验,这些实验证明了我们的方法在定性和定量结果(在几何结构拟合方面)以及计算时间方面的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rolling Shutter Correction in Manhattan World
A vast majority of consumer cameras operate the rolling shutter mechanism, which often produces distorted images due to inter-row delay while capturing an image. Recent methods for monocular rolling shutter compensation utilize blur kernel, straightness of line segments, as well as angle and length preservation. However, they do not incorporate scene geometry explicitly for rolling shutter correction, therefore, information about the 3D scene geometry is often distorted by the correction process. In this paper we propose a novel method which leverages geometric properties of the scene—in particular vanishing directions—to estimate the camera motion during rolling shutter exposure from a single distorted image. The proposed method jointly estimates the orthogonal vanishing directions and the rolling shutter camera motion. We performed extensive experiments on synthetic and real datasets which demonstrate the benefits of our approach both in terms of qualitative and quantitative results (in terms of a geometric structure fitting) as well as with respect to computation time.
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