Implementation of CSR-DCF tracker (#1552)
* Initial commit for CSR-DCF tracker implementation
* Fixes for automatic build
* General code fixes
* Removed unused parameters. Added CSRT to automatic tests.
* Fixed VS build warnings. Fixed a bug with gray sequences.
* Fixed VS build errors for samples file.
* kcf use float data type rather than double.
In our practice, float is good enough and could get better performance.
With this patch, one of my benchmark could get about 20% performance gain.
Signed-off-by: Zhigang Gong <zhigang.gong@intel.com>
* Offload transpose matrix multiplication to ocl.
The matrix multiplication in updateProjectMatrix is one of the
hotspot. And because of the matrix shape is special, say the
m is very short but the n is very large. The GEMM implementation
in neither the clBLAS nor the in trunk implementation are very
inefficient, I implement an standalone transpose matrix mulplication
kernel here. It can get about 10% performance gain on Intel
desktop platform or 20% performance gain on a braswell platform.
And in the mean time, the CPU utilization will be lower.
Signed-off-by: Zhigang Gong <zhigang.gong@intel.com>
* Add verification code for kcf ocl transpose mm kernel.
Signed-off-by: Zhigang Gong <zhigang.gong@linux.intel.com>
* tracking: show FPS in traker sample
* tracking: fix MSVC warnings in KCF
* tracking: move OCL kernel initialization to constructor in KCF
- made some of dependencies explicit
- removed dependencies to highgui and some other modules where possible
- modified some samples to build without modules
* Fix several issues in TrackerMedianFlow implementation
Particularly, add possibility to tune optical flow parameters for a median
flow tracker.
* Improve code of TrackerMedianFlow
Replace a lot of calls of std::vector::erase by one call of
std::remove_if.
* Delete unused code, use norm from OpenCV
* medianFlow:turn getMedian method into function, small code cleanup
* TrackerMedianFlow:fixes in parameters I/O, add test for them
* TrackerMedianFlow:replace double with float in temp buffers
* Fix indentation
* TrackerMedianFlow:add absent parameter case handling in read()
* TrackerMedianFlow:use ROI instead of copy when getting a patch
* TrackerMedianFlow:don't calc image pyramids 2 times
* MedianFlowTracker: use cvIsNan()
* MedianFlow: refactor vector filtration code
* MedianFlow: change if statements layout in filterPointsInVectors
For some applications it is useful to have an estimate of how uncertain
the specific variable is estimated. This could help to act accordingly
e.g. increase the measurement zone if the current estimate is very
uncertain.