Motion estimation from scaled orthographic projections without correspondences

Abstract This paper presents two new eigenstructure-based algorithms for estimating the motion parameters of a rigid object from scaled orthographic projections. The approach requires neither point correspondences between time frames nor between projections at each time. 2D statistics from projections are utilized to recover 3D statistics, which are used for motion estimation. This results in significant speed-up compared to the approach where point correspondences need to be found. The first algorithm is suitable for general point configuration and requires three scaled orthographic projections at each time frame. The second algorithm is suitable for plamar configuration of data points and requires only two orthographic projections at each time instant. Results of simulated and real image experiments demonstrate the performance and efficiency of the algorithms, as well as showing their limitations.