Articulated Multi-Perspective Cameras and Their Application to Truck Motion Estimation

While monocular and stereo camera based motion estimation has reached a level of maturity that enables industrial use, the community keeps exploring novel multi-sensor solutions to meet the high robustness and accuracy requirements of certain applications such as autonomous vehicles. The present paper focuses on motion estimation with multi-perspective camera systems. In particular, we look into the intricate case in which the cameras are distributed over an articulated body, a scenario that occurs in truck motion estimation where additional cameras are installed on the trailer. The resulting articulated multi-perspective camera is analyzed in theory and practice, and we show that-by taking the non-holonomic constraints of the vehicle into account-a single point correspondence measured from the trailer is sufficient to render the additional unknown parameters given by the internal joint configuration before and after a relative displacement fully observable. Optimizing over all parameters enhances the accuracy of the motion estimation of the entire system with respect to using the cameras on each rigid part alone. Results are confirmed on both simulated and real data.