opticalflow

I am working on a project to detect object of interest using background subtraction and track them using optical flow in OpenCV C++. I was able to detect the object of interest using background subtraction. I was able to implement OpenCV Lucas Kanade optical flow on separate program. But, I am stuck at how to these two program in a single program. frame1 holds the actual frame from the video, contours2 are the selected contours from the foreground object. To summarize, how do I feed the forground object obtained from Background subtraction method to the calcOpticalFlowPyrLK ? Or, help me if my

I'm working on a project where I need to implement collision avoidance using OpenCV. This is to be done on iOS (iOS 5 and above will do). Project Objective: The idea is to mount an iPad on the car's dashboard and launch the application. The application should grab frames from the camera and process these to detect if the car is going to collide with any obstacle. I'm a novice to any sort of image processing, hence I'm getting stuck at conceptual levels in this project. What I've done so far: Had a look at OpenCV and read about it on the net. Collision avoidance is implemented using Lukas

I'm trying to perform a complex warp of an image using Dense Optical Flow (I am trying to wap the second image into roughly the same shape as the first image). I'm probably getting this all wrong but Ill post up what I've tried: cv::Mat flow; cv::calcOpticalFlowFarneback( mGrayFrame1, mGrayFrame2, flow, 0.5, 3, 15, 3, 5, 1.2, 0 ); cv::Mat newFrame = cv::Mat::zeros( frame.rows, frame.cols, frame.type() ); cv:remap( frame, newFrame, flow, cv::Mat(), CV_INTER_LINEAR ); The idea if that I am calculating the flow mat from 2 gray scale frames. I get back a flow mat which seems to make sense but now

I'm trying to find python example for computing optical flow with tvl1 opencv function createOptFlow_DualTVL1 but it seems that there isn't enough documentation for it. Could anyone please let me do that? I've used calcOpticalFlowFarneback mentioned here http://docs.opencv.org/master/d7/d8b/tutorial_py_lucas_kanade.html but it is not giving me accurate results, will tvl1 good enough and if not is there another method I should look for? [[EDIT]] I've some regions come from selective search, I want keep only regions with motion in it, so computing the OF for a given frame and then get the avg in

I am working on optical flow, and based on the lecture notes here and some samples on the Internet, I wrote this Python code . All code and sample images are there as well. For small displacements of around 4-5 pixels, the direction of vector calculated seems to be fine, but the magnitude of the vector is too small (that's why I had to multiply u,v by 3 before plotting them). Is this because of the limitation of the algorithm, or error in the code? The lecture note shared above also says that motion needs to be small "u, v are less than 1 pixel", maybe that's why. What is the reason for this