How is the convolution operation carried out when multiple channels are present at the input layer? (e.g. RGB) In such a case you have one 2D kernel per input channel (a.k.a plane). So you perform each convolution (2D Input, 2D kernel) separately and you sum the contributions which gives the final output feature map. Please … Read more
Short version: each keypoint of the first image is matched with a number of keypoints from the second image. We keep the 2 best matches for each keypoint (best matches = the ones with the smallest distance measurement). Lowe’s test checks that the two distances are sufficiently different. If they are not, then the keypoint … Read more
Sample Vision Code Vision Source Code – Carnegie Mellon University Open Source Computer Vision Library – Sourceforge Computer Vision Test Images libsift – Scale-Invariant Feature Transform implementation C# wrapper for OpenCV Resources Computer Vision Online – Computer Vision Online Computer Vision “Home” – Carnegie Mellon University Lecture on Vision Systems – Cardiff School of Computer … Read more
In short: yes. In order to make a mathematical model that can describe a camera with rectangular pixels, you have to introduce two separate focal lengths. I’ll quote from the often recommended “Learning OpenCV” (p. 373) which covers that section pretty well and which I recommend getting if you would like more background on this: … Read more
Disparity Disparity refers to the distance between two corresponding points in the left and right image of a stereo pair. If you look at the image below you see a labelled point X (ignore X1, X2 & X3). By following the dotted line from X to OL you see the intersection point with the left … Read more