3-D Model-Based Multi-Camera Deployment: A Recursive Convex Optimization Approach

Based on a convex optimization approach, we propose a new method of multi-camera deployment for visual coverage of a 3-D object surface. In particular, the optimal placement of a single camera is first formulated as translation and rotation convex optimization problems, respectively, over a set of covered triangle pieces on the target object. The convex optimization is recursively applied to expand the covered area of the single camera, with the initially covered triangle pieces being chosen along the object boundary for the first trial through a selection criterion. Then, the same optimization procedures are applied to place the next camera and thereafter. It is pointed out that our optimization approach guarantees that each camera is placed at the optimal pose in some sense for a group of triangles instead of a single piece. This feature, together with the selection criterion for initially covered triangles, reduces the number of operating cameras while still satisfying various constraint requirements such as resolution, field of view, blur, and occlusion. Both simulation and experimental results are presented to show superior performance of the proposed approach, comparing with the results from other existing methods.