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
Position and vibration control
This is really nice control example on experimental tool developed in our group at Czech Technical University in Prague. The experiment on video deal with oscillation of suspended load during helicopter maneuver. The goal is control the Helicopter position with standard control loops which are conventional in real cases. The second important goal is control vibration of suspended load.Signal Shaper
In this examples is part of our research publicated in such prestigious journals[1] [2].
[1]Vyhlidal T., Hromcik M., Kucera V. Anderle M., On feedback architectures with zero vibration signal, Accepted IEEE Transaction on Automatic Control as regular paper
[2]Vyhlidal T., Kucera V., Hromcik M, Signal shapers with distribute
delays: spectral analysis and design, Automatica, Vol 49, Issue 11, November 2013, pp 3484-3489
Comments
Post a Comment