Robust Parameterization and Computation of the Trifocal Tensor
Philip H. S. Torr, Andrew Zisserman · 1996
The constraint that rigid motion places on the image positions of points and lines over three views is captured by the trifocal tensor. This paper demonstrates a novel robust estimator of the trifocal tensor, based on a minimum number of correspondences across an image triplet. In addition, it is shown how the robust estimate can be used to find a minimal parameterization that enforces the constraints between the elements of the tensor. The matching techniques used to estimate the tensor are both robust (detecting and discarding mismatches) and fully automatic. Results are given for real image sequences. 1 Introduction The trifocal tensor plays a similar role for three views to that played by the fundamental matrix for two. It encapsulates all the (projective) geometric constraints between three views that are independent of scene structure. The tensor only depends on the motion between views and the internal parameters of the cameras, but it can be computed from image corre...