RECOVERY OF 3D MOTION OF A SINGLE-PARTICLE

Abstract

In our previous analysis reported elsewhere, we have shown that 3D velocity of a single point up to a scale factor could be recovered from its 2D trajectory under the perspective projection. We developed a batch method to solve the non-linear regression relation between motion parameters and measurements of projected position. The algorithm was tested on the simulated data and the real images. In this paper, we further extend our work along two directions. First, in order to facilitate the speed of the estimation process we took the recursive approach to estimate the motion parameters. Second, we investigate the performance degradation due to two classes of model mismatch: parameter jumping and undermodeling. Then we propose the Finite Lifetime Alternately Triggered Multiple Model Filter (FLAT MMF), as a solution. A number of experiments are conducted to illustrate the performance degradation due to the model mismatches and the performance improvement as the proposed FLAT MMF is used.