I have a visual odometry routine where I am attempting to perform inlier detection.
I have an nxn square cv::Mat consistency matrix, where cell ij is 1 if the absolute distance difference between the matches in their unique 3D frames (prior and current) is below some threshold. See "Real-Time Stereo Visual Odometry for Autonomous Ground Vehicles" by Andrew Howard, JPL (2008) for more details.
Anyway,
I want to find the node (match) of this matrix with the maximum degree. My matrix is upper triangular and this means that for every ij where i = j, I need the sum of row i + col j (or equivalently, degree i = sum row i + sum col i).
This can certainly be accomplished with some loops, but my question is, are there built in OpenCV functions that I can make use of to create cleaner code, without having to write my own?