Affine optic flow

버전 1.3.0.0 (1.03 MB) 작성자: David Young
Estimates the parameters of an affine (first-order) optic flow model from two images.

다운로드 수: 6.6K

업데이트 날짜: 2016/3/4

라이선스 보기

An affine (or first-order) optic flow model has 6 parameters, describing image translation, dilation, rotation and shear. The class affine_flow provides methods to estimates these parameters for two frames of an image sequence.
The class implements a least-squares fit of the parameters to estimates of the spatial and temporal grey-level gradients. This is an extension of the well-known Lucas-Kanade method. The images are either sampled conventionally, on a rectilinear grid, or on a log-polar grid. In the latter case, the class may iteratively refine its estimates by moving the sampling grid to track the motion. Options to specify a region of interest and smoothing and sampling parameters are provided.
The file includes a demonstration of the class, and test images for this. The functions for smoothing images and estimating gradients may be useful independently, and log-polar sampling functions are included (and are available separately in submission 27023).

인용 양식

David Young (2022). Affine optic flow (https://www.mathworks.com/matlabcentral/fileexchange/27093-affine-optic-flow), MATLAB Central File Exchange. 검색됨 .

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개발 환경: R2016a
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