opticalflow

Lots of resources say that there are two types optical flow algorithms. And Lucas-Kanade is a sparse technique, but I can't find the meanings of sparse and dense? Can some one tell me what is the difference between dense and sparse optical flow? Rui Marques The short explanation is, sparse techniques only need to process some pixels from the whole image, dense techniques process all the pixels. Dense techniques are slower but can be more accurate, but in my experience Lucas-Kanade accuracy might be enough for real-time applications. An example of a dense optical flow algorithm (the most

I'm working on an augmented reality app for iPhone that involves a very processor-intensive object recognition algorithm (pushing the CPU at 100% it can get through maybe 5 frames per second), and in an effort to both save battery power and make the whole thing less "jittery" I'm trying to come up with a way to only run that object recognizer when the user is actually moving the camera around. My first thought was to simply use the iPhone's accelerometers / gyroscope, but in testing I found that very often people would move the iPhone at a consistent enough attitude and velocity that there

I have been looking to extract velocity vectors of every pixels b/n two frames. I used the opencv function as flows: calcOpticalFlowFarneback(Previous_Gray, Current_Gray, Optical_Flow, 0.5, 3, 15, 3, 5, 1.2, 0); Previous_Gray = previous frame Current_Gray = current frame And it gives me the array in the 3rd argument Optical_Flow but I can't really tell how to extract the velocity vectors using this array. Thanks in Advance. Dawit Mat& flow: The computed flow image; will have the same size as prevImg and type CV_32FC2 This type means that you have 2 float variables (presumed x and y) for each

I am doing a project to find the speed of a vehicle from images. We are taking these images from within the vehicle. We will be marking some object from the 1st image as a reference. Using the properties of the same object in the next image, we must calculate the speed of the moving vehicle. Can anyone help me here??? I am using python opencv. I have succeeded till finding the marked pixel in the 2nd image using Optical flow method. Can anyone help me with the rest? Knowing the acquisition frequency, you must now find the distance between the successive positions of the marker. To find this

I am new to Qt, I only know the basics: create interfaces and connect slots. In a few words, my knowledge is not deep at all. I need to open a video file and capture all of its frames to get the R, G, B channels and, later on, process optical flow (this is already done) frame to frame to finally represent it on a window. Is it possible to get the video frames with Qt? I have researched a lot but not found anything conclusive. You can use QMediaPlayer to achieve this. Instantiate the QMediaPlayer . Subclass the QAbstractVideoSurface . Set your implementation as the output for the media player

I am using createOptFlow_DualTVL1() to calculate optical flow which is giving me exactly what I want but it is very slow. Is there any way I can speed it up a little bit or is there any other optical flow function which will give me the same result with less processing time? I have used calcOpticalFlowFarneback() , cvGoodFeaturesToTrack() but the quality is not good. please help. Thank you in advance Below is how I apply createOptFlow_DualTVL1() Ptr<DenseOpticalFlow> tvl1 = createOptFlow_DualTVL1(); tvl1->calc(Previous_Gray_Frame, Current_Gray_Frame, Optical_Flow); In order to speed up the