Acquisition of translational motion by the parallel trinocular

This study presents a technique for recovering translational motion parameters using a parallel trinocular system and a least squares estimation scheme. The proposed approach overcomes the matrix singularity problem encountered when attempting to recover the motion parameters using a binocular scheme. To further reduce the computational complexity of the motion estimation process, the study also presents a compact closed-form scheme for estimating the translational motion parameters. The closed-form algorithm not only resolves the matrix singularity problem, but also avoids the requirement for matrix manipulation. As a result, it has a low computational complexity and is therefore an ideal solution for performing motion estimation in complex, real-world visual imaging applications. The performance of the closed-form algorithm is evaluated by performing a series of numerical simulations in which translational motions of various magnitudes and in various directions are recovered in both noise-free and perturbed environments. In general, the results demonstrate that the translational motion parameters can be accurately reconstructed provided that the motion in the depth direction is limited to small displacements only. Overall, the simulation results suggest that the parallel trinocular system and the motion parameter estimation scheme presented in this study represent a suitable basis for the development of artificial planar-array compound-like eyes for enhanced performance tracking and imaging applications.