matlab-cvst

I currently have a stereo camera setup. I have calibrated both cameras and have the intrinsic matrix for both cameras K1 and K2 . K1 = [2297.311, 0, 319.498; 0, 2297.313, 239.499; 0, 0, 1]; K2 = [2297.304, 0, 319.508; 0, 2297.301, 239.514; 0, 0, 1]; I have also determined the Fundamental matrix F between the two cameras using findFundamentalMat() from OpenCV. I have tested the Epipolar constraint using a pair of corresponding points x1 and x2 (in pixel coordinates) and it is very close to 0 . F = [5.672563368940768e-10, 6.265600996978877e-06, -0.00150188302445251; 6.766518121363063e-06, 4

Calibration: I have calibrated the camera using this vision toolbox in Matlab. I used checkerboard images to do so. After calibration I get the cameraParams which contains: Camera Extrinsics RotationMatrices: [3x3x18 double] TranslationVectors: [18x3 double] and Camera Intrinsics IntrinsicMatrix: [3x3 double] FocalLength: [1.0446e+03 1.0428e+03] PrincipalPoint: [604.1474 359.7477] Skew: 3.5436 Aim: I have recorded trajectories of some objects in motion using this camera. Each object corresponds to a single point in a frame. Now, I want to project the points such that I get a top-view. Note all

I read some works about Kalman filter for CV object tracking but I can't find some reference about the choice of: 1)the process noise covariance Q; 2)Measurement noise covariance R. So far I have realized that the model is equation of motion (someone uses acceleration as state variable, others use position and speed only) but nobody is clear about Q and R choice including this example by mathworks: http://www.mathworks.it/it/help/vision/examples/using-kalman-filter-for-object-tracking.html Recently I found this page: http://blog.cordiner.net/2011/05/03/object-tracking-using-a-kalman-filter

I have to perform re-projection of my 3D points (I already have data from Bundler). I am using Camera Calibration toolbox in MATLAB to get the intrinsic camera parameters. I got output like this from 27 images (chess board; images are taken from different angles). Calibration results after optimization (with uncertainties): Focal Length: fc = [ 2104.11696 2101.75357 ] ± [ 23.13283 22.92478 ] Principal point: cc = [ 969.15779 771.30555 ] ± [ 21.98972 15.25166 ] Skew: alpha_c = [ 0.00000 ] ± [ 0.00000 ] Distortion: kc = [ 0.11555 -0.55754 -0.00100 -0.00275 0.00000 ] ± [ >0.05036 0.59076 0.00307

This is easy to do in OpenCV however I would like a native Matlab implementation that is fairly efficient and can be easily changed. The method should be able to take the camera parameters as specified in the above link. You can now do that as of release R2013B, using the Computer Vision System Toolbox. There is a GUI app called Camera Calibrator and a function undistortImage . The simplest and most common way of doing undistort (also called unwarp or compensating for lens distortion) is to do a forward distortion on a chosen output photo size and then a reverse mapping using bilinear

I'm implementing Bag Of Words in opencv by using SIFT features in order to make a classification for a specific dataset. So far, I have been apple to cluster the descriptors and generate the vocabulary. As I know, I have to train SVM ... but i have some questions which i'm really confused about them. The major problem is the concept behind the implementations, these are my questions: 1- When I extract the features and then create the vocabulary, shall I extract the features for all the objects (let's say 5 objects)and put them in one file, so I make all of them in a one vocabulary file that

I'm using Matlab to show the frames in a video sequence , below is my code: seq=sprintf('walk%d.avi',v); % video's name videoReader = vision.VideoFileReader(seq); vidObj = VideoReader(seq); numFrames = vidObj.NumberOfFrames for i = 1:numFrames frame = step(videoReader); % read the next video frame imshow(frame) end Actually it worked fine previously, and i have no idea since when and what caused it to show rotated image . Hope you guys can help me. thank you. Most updated Matlab function to vertically flip back the frame is: FlippedFrame = flip(frame,1); 来源： https://stackoverflow.com/questions

I have segmented results in a folder. Those need to be read in a for loop and processed further in the loop. I tried reading as below: for i=1:10 file_name=dir(strcat('C:\Users\adminp\Desktop\dinosaurs\')); im=imread(strcat('C:\Users\adminp\Desktop\dinosaurs\',file_name(i).name)); %processing of read image end An error was thrown :??? Error using ==> imread at 370 Can't open file "C:\Users\adminp\Desktop\dinosaurs\." for reading; you may not have read permission. Please suggest where I have gone wrong. I guess your problem is that: file_name(1).name = . % Stands for current directory file_name