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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Optic flow ： ウィキペディア英語版 Optical flow Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene. The concept of optical flow was introduced by the American psychologist James J. Gibson in the 1940s to describe the visual stimulus provided to animals moving through the world. Gibson stressed the importance of optic flow for affordance perception, the ability to discern possibilities for action within the environment. Followers of Gibson and his ecological approach to psychology have further demonstrated the role of the optical flow stimulus for the perception of movement by the observer in the world; perception of the shape, distance and movement of objects in the world; and the control of locomotion. The term optical flow is also used by roboticists, encompassing related techniques from image processing and control of navigation including motion detection, object segmentation, time-to-contact information, focus of expansion calculations, luminance, motion compensated encoding, and stereo disparity measurement. == Estimation == Sequences of ordered images allow the estimation of motion as either instantaneous image velocities or discrete image displacements.〔 Fleet and Weiss provide a tutorial introduction to gradient based optical flow . John L. Barron, David J. Fleet, and Steven Beauchemin provide a performance analysis of a number of optical flow techniques. It emphasizes the accuracy and density of measurements. The optical flow methods try to calculate the motion between two image frames which are taken at times ''t'' and $t+\backslash Delta\; t$ at every voxel position. These methods are called differential since they are based on local Taylor series approximations of the image signal; that is, they use partial derivatives with respect to the spatial and temporal coordinates. For a 2D+''t'' dimensional case (3D or ''n''-D cases are similar) a voxel at location $(x,y,t)$ with intensity $I(x,y,t)$ will have moved by $\backslash Delta\; x$, $\backslash Delta\; y$ and $\backslash Delta\; t$ between the two image frames, and the following ''brightness constancy constraint'' can be given: :$I(x,y,t)\; =\; I(x+\backslash Delta\; x,\; y\; +\; \backslash Delta\; y,\; t\; +\; \backslash Delta\; t)$ Assuming the movement to be small, the image constraint at $I(x,y,t)$ with Taylor series can be developed to get: :$I(x+\backslash Delta\; x,y+\backslash Delta\; y,t+\backslash Delta\; t)\; =\; I(x,y,t)\; +\; \backslash frac\backslash Delta\; x+\backslash frac\backslash Delta\; y+\backslash frac\backslash Delta\; t+$H.O.T. From these equations it follows that: :$\backslash frac\backslash Delta\; x+\backslash frac\backslash Delta\; y+\backslash frac\backslash Delta\; t\; =\; 0$ or :$\backslash frac\backslash frac+\backslash frac\backslash frac+\backslash frac\backslash frac\; =\; 0$ which results in :$\backslash fracV\_x+\backslash fracV\_y+\backslash frac\; =\; 0$ where $V\_x,V\_y$ are the $x$ and $y$ components of the velocity or optical flow of $I(x,y,t)$ and $\backslash tfrac$, $\backslash tfrac$ and $\backslash tfrac$ are the derivatives of the image at $(x,y,t)$ in the corresponding directions. $I\_x$,$I\_y$ and $I\_t$ can be written for the derivatives in the following. Thus: :$I\_xV\_x+I\_yV\_y=-I\_t$ or :$\backslash nabla\; I^T\backslash cdot\backslash vec\; =\; -I\_t$ This is an equation in two unknowns and cannot be solved as such. This is known as the ''aperture problem'' of the optical flow algorithms. To find the optical flow another set of equations is needed, given by some additional constraint. All optical flow methods introduce additional conditions for estimating the actual flow. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Optical flow」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.