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
Opencv Kalman filter example video head tracking
Example of kalman filter in Opencv with head detection and tracking.
Two big tutorials will be published soon.
- New version of LBP cascades for people detection, head detection
- Code and tutorial related to this example. Simple kalman filter for tracking in Opencv. I just finished the code for you.. Stay tuned and share :). Thanks
Hello! where can i find the tutorial?
ReplyDeleteCan i get the tutorial Sir?
ReplyDeletecan i get a code please!
ReplyDeleteWhere can i find the tutorial?
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