http://www.emgu.com

The OpticalFlow type exposes the following members.

Methods

  NameDescription
Public methodStatic memberBM
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)
Public methodStatic memberDualTVL1
Dual TV L1 Optical Flow Algorithm.
Public methodStatic memberFarneback
Computes dense optical flow using Gunnar Farneback's algorithm
Public methodStatic memberHS
Computes flow for every pixel of the first input image using Horn & Schunck algorithm
Public methodStatic memberLK
Computes flow for every pixel of the first input image using Lucas & Kanade algorithm
Public methodStatic memberPyrLK(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
Public methodStatic memberPyrLK(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

See Also