Robust optical flow field estimating method based on TV-L1 variation model

Abstract

The invention discloses a robust optical flow field estimating method based on a TV-L1 variation model. The robust optical flow field estimating method comprises the following steps: firstly, performing structural texture resolution on an input image, and establishing an optical flow calculating model based on the TV-L1; secondly, establishing an image pyramid, calculating optical flow on the lowest image resolution layer by a discretized alternating iteration method, further calculating with a calculated value as an initial value of a next higher resolution layer till the highest resolution layer, namely the original image resolution, and accelerating the algorithm by using a GPU (graphic processing unit) so as to improve the instantaneity of the algorithm; finally, calculating the error of the algorithm by using an optical flow error evaluating function. In the robust optical flow field estimating method, the input image is processed by a structural texture resolving method and a texture image is applied to optical flow calculation, so that influence of an image shadow caused by illumination variation on the calculation is avoided; by the robust optical flow field estimating method based on the TV-L1 variation model, segmenting smoothness of the image is kept and the optical flow calculating precision and optical flow calculating speed are improved.

Description

technical field [0001] The invention belongs to the field of computer vision and relates to a TV-L based 1 (First-Order Data Items) Method for Robust Optical Flow Field Estimation for Variational Models. Background technique [0002] Optical flow refers to the instantaneous speed of pixel movement of space moving objects on the observation imaging plane, which contains the information of moving objects, so it can be used to understand the movement of objects. Optical flow includes the following three elements: one is the movement that causes the optical flow, that is, the velocity field; the other is the carrier that can carry information and has optical characteristics, such as pixels with grayscale; the third is to move the object from The scene is projected onto the image plane so that objects can be observed as imaged projections. Optical flow computing is one of the important research fields of computer vision and image processing, and has a wide range of applications...

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Problems solved by technology

[0011] The patent with the application number 201310174158.6 proposes a fast optical flow field calculation method based on error distributed multi-layer grids. To solve the real-time problem of optical flow calculation, the multi-grid method is used to solve the energy model, but the The method uses the basic optical flow calculation model, but only improves the calculation speed in the solution algorithm, and does not improve the model

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