﻿OpticalFlow Members
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The OpticalFlow type exposes the following members.

# Methods

NameDescription
BM
Calculates optical flow for overlapped blocks block_size.width * block_size.height pixels each, thus the velocity fields are smaller than the original images. For every block in prev the functions tries to find a similar block in curr in some neighborhood of the original block or shifted by (velx(x0,y0),vely(x0,y0)) block as has been calculated by previous function call (if use_previous)
Farneback
Computes dense optical flow using Gunnar Farneback's algorithm
HS
Computes flow for every pixel of the first input image using Horn & Schunck algorithm
LK
Computes flow for every pixel of the first input image using Lucas & Kanade algorithm
PyrLK(Image<(Of <<'(Gray, Byte>)>>), Image<(Of <<'(Gray, Byte>)>>), array<PointF>[]()[][], Size, Int32, MCvTermCriteria, array<PointF>[]()[][]%, array<Byte>[]()[][]%, array<Single>[]()[][]%)
Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids
PyrLK(Image<(Of <<'(Gray, Byte>)>>), Image<(Of <<'(Gray, Byte>)>>), Image<(Of <<'(Gray, Byte>)>>), Image<(Of <<'(Gray, Byte>)>>), array<PointF>[]()[][], Size, Int32, MCvTermCriteria, LKFLOW_TYPE, array<PointF>[]()[][]%, array<Byte>[]()[][]%, array<Single>[]()[][]%)
Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids