Search Results

Search found 3 results on 1 pages for 'opticalflow'.

Page 1/1 | 1 

  • Using Optical Flow in EmguCV

    - by Meko
    HI. I am trying to create simple touch game using EmguCV.Should I use optical flow to determine for interaction between images on screen and with my hand ,if changes of points somewhere on screen more than 100 where the image, it means my hand is over image? But how can I track this new points? I can draw on screen here the previous points and new points but It shows on my head more points then my hand and I can not track my hands movements. void Optical_Flow_Worker(object sender, EventArgs e) { { Input_Capture.SetCaptureProperty(Emgu.CV.CvEnum.CAP_PROP.CV_CAP_PROP_POS_FRAMES, ActualFrameNumber); ActualFrame = Input_Capture.QueryFrame(); ActualGrayFrame = ActualFrame.Convert<Gray, Byte>(); NextFrame = Input_Capture.QueryFrame(); NextGrayFrame = NextFrame.Convert<Gray, Byte>(); ActualFeature = ActualGrayFrame.GoodFeaturesToTrack(500, 0.01d, 0.01, 5); ActualGrayFrame.FindCornerSubPix(ActualFeature, new System.Drawing.Size(10, 10), new System.Drawing.Size(-1, -1), new MCvTermCriteria(20, 0.3d)); OpticalFlow.PyrLK(ActualGrayFrame, NextGrayFrame, ActualFeature[0], new System.Drawing.Size(10, 10), 3, new MCvTermCriteria(20, 0.03d), out NextFeature, out Status, out TrackError); OpticalFlowFrame = new Image<Bgr, Byte>(ActualFrame.Width, ActualFrame.Height); OpticalFlowFrame = NextFrame.Copy(); for (int i = 0; i < ActualFeature[0].Length; i++) DrawFlowVectors(i); ActualFrameNumber++; pictureBox1.Image = ActualFrame.Resize(320, 400).ToBitmap() ; pictureBox3.Image = OpticalFlowFrame.Resize(320, 400).ToBitmap(); } } private void DrawFlowVectors(int i) { System.Drawing.Point p = new Point(); System.Drawing.Point q = new Point(); p.X = (int)ActualFeature[0][i].X; p.Y = (int)ActualFeature[0][i].Y; q.X = (int)NextFeature[i].X; q.Y = (int)NextFeature[i].Y; p.X = (int)(q.X + 6 * Math.Cos(angle + Math.PI / 4)); p.Y = (int)(q.Y + 6 * Math.Sin(angle + Math.PI / 4)); p.X = (int)(q.X + 6 * Math.Cos(angle - Math.PI / 4)); p.Y = (int)(q.Y + 6 * Math.Sin(angle - Math.PI / 4)); OpticalFlowFrame.Draw(new Rectangle(q.X,q.Y,1,1), new Bgr(Color.Red), 1); OpticalFlowFrame.Draw(new Rectangle(p.X, p.Y, 1, 1), new Bgr(Color.Blue), 1); }

    Read the article

  • Finding distance travelled by robot using Optical Flow

    - by user280454
    Hi, I'm working on a project right now in which we are developing an autonomous robot. I have to basically find out the distance travelled by the robot between any 2 intervals. I'm using OpenCV, and using the Optical Flow functions of OpenCV, I'm able to find out the velocity/distance of each pixel in 2 different images. Using this information, I want to be able to find out the distance travelled by the robot in the interval between those 2 images. I thought of a way in which we could develop an input output mapping between the distance travelled by pixels and the distance travelled by the bot (using some tests). In this way, using neural networks, we would be able to find the relationship. However, the optical flow would depend on the distance of the camera from the pixel, which would cause problems. Is there any way to solve this problem?

    Read the article

  • Fast, very lightweight algorithm for camera motion detection?

    - by Ertebolle
    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 wouldn't be any way to tell that it was still in motion. So that left the option of analyzing the actual video feed and detecting movement in that. I got OpenCV working and tried running their pyramidal Lucas-Kanade optical flow algorithm, which works well but seems to be almost as processor-intensive as my object recognizer - I can get it to an acceptable framerate if I lower the depth levels / downsample the image / track fewer points, but then accuracy suffers and it starts to miss some large movements and trigger on small hand-shaking-y ones. So my question is, is there another optical flow algorithm that's faster than Lucas-Kanade if I just want to detect the overall magnitude of camera movement? I don't need to track individual objects, I don't even need to know which direction the camera is moving, all I really need is a way to feed something two frames of video and have it tell me how far apart they are.

    Read the article

1