seveque's profile - activity

Thanks, Kirill, for pointing out that the InputArray type in the current API will allow passing an array of image pairs as input to the stereo matching algorithms. I'll consider modifying the source code to handle this situation as you suggest!

Jacek, thanks for your response. I guess you are right that the stereo algorithms currently available in OpenCV do not allow mulitple image pairs as input. As you point out, it may be possible to modify the SGBM implementation to do multiple passes across each image pair during the computation of the pixel matching score.

As far as I know, most people who implement this technique use the sum of scores across all the image pairs. Taking the minimum score doesn't seem like it would be appropriate - in a set of RGB image pairs, for example, two pixels may be very different colors but still match perfectly within a single spectral channel.

I don't want to use just 3 channels of RGB images. Rather, I would like to be able to use an arbitrary number of image pairs to compute the stereo matching score that is used to generate the final disparity map. This technique is known as "spacetime stereo", and there are a number of research papers that discuss the method and demonstrate its effectiveness.

Calling the OpenCV stereo matching function multiple times does not accomplish what I want. I want to use multiple image pairs as input to the stereo pixel matching metric and then to create a single disparity map as output.

Victor,

Thanks for your idea about masking parts of the image pairs and merging the results after processing.

However, I'd like to use all of the image pairs simultaneously in the computation of the stereo matching cost metric for each pixel (ala "space-time stereo" techniques). Each image pair contains potentially useful information for each pixel, the image pairs just vary in the wavelength of light or pattern of projected illumination.

I would like to use the OpenCV stereo matching algorithms (such as StereoSGBM) with more than one pair of images. I have several pairs of images taken from the same position, but with varying illumination conditions.

Is there an easy way to use the stereo matching algorithms with more than one image pair? I realize that some of the stereo algorithms work on 3-channel images, which would allow encodings of up to 3 1-channel images, but my images are already 3-channel RGB, and I have more than 3 pairs that I'd like to use to compute the matching costs, if possible.

I'd appreciate any ideas on the simplest way to use multiple image pairs with the stereo algorithms. Thank you!