Dense Optical Flow

Dense optical flow algorithms compute motion for each point

calcOpticalFlowSF

Calculate an optical flow using “SimpleFlow” algorithm.

C++: void calcOpticalFlowSF(InputArray from, InputArray to, OutputArray flow, int layers, int averaging_block_size, int max_flow)

C++: calcOpticalFlowSF(InputArray from, InputArray to, OutputArray flow, int layers, int averaging_block_size, int max_flow, double sigma_dist, double sigma_color, int postprocess_window, double sigma_dist_fix, double sigma_color_fix, double occ_thr, int upscale_averaging_radius, double upscale_sigma_dist, double upscale_sigma_color, double speed_up_thr)

Parameters:

• prev – First 8-bit 3-channel image.
• next – Second 8-bit 3-channel image of the same size as prev
• flow – computed flow image that has the same size as prev and type CV_32FC2
• layers – Number of layers
• averaging_block_size – Size of block through which we sum up when calculate cost function for pixel
• max_flow – maximal flow that we search at each level
• sigma_dist – vector smooth spatial sigma parameter
• sigma_color – vector smooth color sigma parameter
• postprocess_window – window size for postprocess cross bilateral filter
• sigma_dist_fix – spatial sigma for postprocess cross bilateralf filter
• sigma_color_fix – color sigma for postprocess cross bilateral filter
• occ_thr – threshold for detecting occlusions
• upscale_averaging_radius – window size for bilateral upscale operation
• upscale_sigma_dist – spatial sigma for bilateral upscale operation
• upscale_sigma_color – color sigma for bilateral upscale operation
• speed_up_thr – threshold to detect point with irregular flow - where flow should be recalculated after upscale

See [Tao2012]. And site of project - http://graphics.berkeley.edu/papers/Tao-SAN-2012-05/.

Note

• An example using the simpleFlow algorithm can be found at samples/simpleflow_demo.cpp

optflow::OpticalFlowDeepFlow

DeepFlow optical flow algorithm implementation.

class optflow::OpticalFlowDeepFlow : public DenseOpticalFlow

The class implements the DeepFlow optical flow algorithm described in [Weinzaepfel2013] . See also http://lear.inrialpes.fr/src/deepmatching/ .

Parameters - class fields - that may be modified after creating a class instance:

float alpha

Smoothness assumption weight

float delta

Color constancy assumption weight

float gamma

Gradient constancy weight

float sigma

Gaussian smoothing parameter

int minSize

Minimal dimension of an image in the pyramid (next, smaller images in the pyramid are generated until one of the dimensions reaches this size)

float downscaleFactor

Scaling factor in the image pyramid (must be < 1)

int fixedPointIterations

How many iterations on each level of the pyramid

int sorIterations

Iterations of Succesive Over-Relaxation (solver)

float omega

Relaxation factor in SOR

optflow::createOptFlow_DeepFlow

Create an OpticalFlowDeepFlow instance

C++: Ptr<DenseOpticalFlow> optflow::createOptFlow_DeepFlow()

Returns a pointer to a DenseOpticalFlow instance - see DenseOpticalFlow::calc()

[Tao2012]

Michael Tao, Jiamin Bai, Pushmeet Kohli and Sylvain Paris. SimpleFlow: A Non-iterative, Sublinear Optical Flow Algorithm. Computer Graphics Forum (Eurographics 2012)

[Weinzaepfel2013]

Weinzaepfel, J. Revaud, Z. Harchaoui, and C. Schmid, “DeepFlow: Large Displacement Optical Flow with Deep Matching,” 2013 IEEE Int. Conf. Comput. Vis., pp. 1385–1392, Dec. 2013.