A methodology for multi-camera surface-shape estimation of deformable unknown objects

Abstract

A novel methodology is proposed herein to estimate the three-dimensional (3D) surface shape of unknown, markerless deforming objects through a modular multi-camera vision system. The methodology is a generalized formal approach to shape estimation for a priori unknown objects. Accurate shape estimation is accomplished through a robust, adaptive particle filtering process. The estimation process yields a set of surface meshes representing the expected deformation of the target object. The methodology is based on the use of a multi-camera system, with a variable number of cameras, and range of object motions. The numerous simulations and experiments presented herein demonstrate the proposed methodology's ability to accurately estimate the surface deformation of unknown objects, as well as its robustness to object loss under self-occlusion, and varying motion dynamics.