J. Zhao, W. Xu, and L. Kneip. A certifiably globally optimal solution to generalized essential matrix estimation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 2020b
We present a convex optimization approach for generalized essential matrix (GEM) estimation. Our proposed non-minimal solver minimizes the sum of squared residuals by reformulating the problem as a quadratically constrained
quadratic program.
Link to our lab's webpage:
http://mpl.sist.shanghaitech.edu.cn
