Performance improvement of metric reconstruction based on partial joint diagonalization

Self-calibration is one of powerful tools in the field of computer vision such as 3-D shape reconstruction and camera motion reconstruction. Self-calibration consists of two main parts. One is projective reconstruction and the other is metric reconstruction. The latter one can be reduced to a problem to find a matrix that satisfies some absolute dual quadric (ADQ) constraint. However, it is difficult to formulate the problem with considering the constraint strictly, which may make the final result such as reconstructed 3-D shapes unstable. In this paper, we propose a novel method for metric reconstruction incorporating a partial joint diagonalization of symmetric matrices. Some results of computer simulations are also given to verify the efficacy of the proposed method.