From Optical Flow to Image Deformations

本研究旨在证明视觉运动分析可以通过以下方式得到改进：（1）用图像变形（它们之间的相对运动）的分析代替光流（图像点的运动）的分析;（2）跨越更宽的视场。图像变形的优点类似于差分放大器在噪声背景中检测弱信号的优点：如果噪声对两个输入的影响相等，则通过取其差值来消除。在类比中，由摄像机旋转引起的图像运动是噪声，而由平移引起的图像运动是有用信号。至于视场，文献表明，60度或更大的视角几乎导致重建问题的条件的量子改进。这一领先地位正在追求的理论和实证研究的形状重建从相机运动引起的广角图像的变形。图像变形和宽视场这两个概念在初步研究中已经证明是成功的，目前正在进行理论和实验研究。最后的贡献将是一个多帧的形状和运动重建方法，工作可靠，透视图像。

This research aims at demonstrating that visual motion analysis can be improved (1) by replacing the analysis of optical flow (the motion of image points) with that of image deformations (their motion relative to each other) and (2) by spanning a wider field of view. The advantages of image deformations are akin to those of differential amplifiers for the detection of weak signals in a noisy background: if noise affects both inputs equally, it is canceled by taking their difference. In the analogy, image motion caused by camera rotation is the noise, and that caused by translation is the useful signal. As to the field of view, the literature shows that a viewing angle of 60 degrees or more leads almost to a quantum improvement in the conditioning of the reconstruction problem. This lead is being pursued by a theoretical and empirical investigation of shape reconstruction from the deformations of wide-angle images induced by camera motion. The two ideas of image deformations and a wide field of view, already proven successful in preliminary studies, are being investigated theoretically and experimentally. The final contribution will be a multiframe shape and motion reconstruction method that works reliably and for perspective images.