[−][src]Function opencv::optflow::calc_optical_flow_sf_1
pub fn calc_optical_flow_sf_1(
from: &dyn ToInputArray,
to: &dyn ToInputArray,
flow: &mut dyn ToOutputArray,
layers: i32,
averaging_block_size: i32,
max_flow: i32,
sigma_dist: f64,
sigma_color: f64,
postprocess_window: i32,
sigma_dist_fix: f64,
sigma_color_fix: f64,
occ_thr: f64,
upscale_averaging_radius: i32,
upscale_sigma_dist: f64,
upscale_sigma_color: f64,
speed_up_thr: f64
) -> Result<()>
Calculate an optical flow using "SimpleFlow" algorithm.
Parameters
- from: First 8-bit 3-channel image.
- to: 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