Rakefetmoor's profile - activity

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Hi,

I have two images that are partially overlapping. I know the projection matrix for each of the images. I would like to check if the images are well aligned to each other. I was thinking to do the following steps: find the similar features find the features' world coordinates calculate the distances between each pair of the corresponding features. I wonder if there is a quicker way to check if the images are aligned. Let's assume that I marked one feature in one of the images so I know [x, y, z, i, j]. Is there a way to find what is the corresponding feature in the other image?

Thanks in advance for any leading answers.

Hi, I am using SURF with the default parameter to detect features in two images of urban area. Those images were taken with the same camera in different view angles. I plot the images with the key points and I see that the keypoints are on the ground as well as on the building tops. When I match the features between the two images with brute force matcher that picks the two near neighboars and use the ratio test of 0.7 threshold as well as the symmetry test, all the matches that left are on the ground. I loosed the constrain and I am getting more outliers but still all the matches points are on the ground. Do you have any suggestions why this is happening? I am interested to have matching points on the roof tops of the buildings and I am wondering if the parameter choice prompt the matches to be on a flat area. I'll appretiate any feedback.

I have an image with N points which I know (I, j, x, y, z). I calculated the perspective matrix M(4,4) that transforms any x,y,z to the image I,j. What will be the matrix to transform from I,J to xyz. Do I have all the information to generate this matrix?

Thanks

what information can I get about the camera if I know the image size (x,y) in pixels as well as the pixel size (x,y) in mm? The knowledge I have is that the image was taken from nadir. I am trying to find out what is the minimum data I need to know about the camera to figure out the camera parameters.

Thank you in advance.

I have an image with N points which I know (I, j, x, y, z). I calculated the perspective matrix (4,4) that transforms any x,y,z to the image I,j. I don't know anything about the camera that generates the image. Is there a way to calculate the location of the camera from the perspective matrix? I want to know the rotation angles of the camera (rolll, pitch, heading) and the translation tx, Ty, tz. Also, how can I get the camera intrinsic matrix? I'll appreciate any leads.

thanks you so much.

You can resize the image: DEC- the decimating factor int row = img_full.rows/DEC; int col = img_full.cols/DEC; Mat img cv::resize(img_full, img, Size(col, row));

I found matches between two images using BruteForceMatcher and knnMatch. The features in each image were generated by SURF or BRISK. I filtered out some of the matches by using the ratio test of the distances between the test feature and the second nearest neighbor. What I want to do is draw the matches between the two images so I can see if the points are indeed match. The problem is that I have way too many matches points (~2000). The features are not on a flat surface so I can not use getHomography to filter out the outliers. Is there a way to find the best N matches?

Thanks,

I have 5 oblique images and one ortho image, all generated from the same camera and all cover the same scene. I want to align the oblique images to the ortho image. I found good matches from each oblique image to the ortho image. I used findHomography function to find matrix H for each image. My questions are: Can I get from H the camera's position for each image relative to the camera's position in the ortho image? Do I had enough data to figure out the camera parameters?

Any leads to help me will be much appreciated!

Thanks