This OpenCV tutorial is a very simple code example of GPU Cuda optical flow in OpenCV written in c++. The configuration of the project, code, and explanation are included for farneback Optical Flow method. Farneback algorithm is a dense method that is used to process all the pixels in the given image. The dense methods are slower but more accurate as all the pixels of the image are processed. In the following example, I am displaying just a few pixes based on a grid. I am not displaying all the pixes. In the opposite to dense method the sparse method like Lucas Kanade using just a selected subset of pixels. They are faster. Both methods have specific applications. Lucas-Kanade is widely used in tracking. The farneback can be used for the analysis of more complex movement in image scene and furder segmentation based on these changes. As dense methods are slightly slower, the GPU and Cuda implementation can lead to great performance improvements to calculate optical flow for all pixels o
Face features detection testing clandmark
I like this project because some of the authors also teach me at CTU in Prague. This is just basic models free to use and test in Clandmark.
I would like to pusblish tutorial how to use clandmark on my blog
http://funvision.blogspot.com
Need some time for basic research. I had not so well results under Visual Studio on windows. The optimization method is sensitive to precision of float type. I increase that precision by replacing one type inside the solver.. There is certainly smarter way how to achieve better results.
You can download this product and test it as well from here. http://cmp.felk.cvut.cz/~uricamic/clandmark/
Comments
Post a Comment