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
Research AI and Computer vision
There is some demo. Actually it works. I am younger and good thing is that gender is right.
Project oxford
This is great project from Microsoft research.. The computer vision SDK and API of a state-of-the-art image algorithms. Gender classification optical letter Recognition and many more.
Face DetectionFace VerificationEmotion RecognitionFace TrackingMotion DetectionStabilizationSpeech to TextText to SpeechSpeaker IdentificationSpeaker VerificationSpell CheckWord Breaking
More information about microsoft computer vision research you can find here research microsoft
There are project for images understanding like microsoft Coco i mentioned in some pervious articles (More about Coco). Another projects like Human behavior and video understanding, also 3D modelling and machine learning optimization and many more articles, source code and ideas. The lots of informations are related to Kinect and RGBD.
thank u blogger
ReplyDeleteThis comment has been removed by the author.
ReplyDelete