PROJECT TITLE :

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

ABSTRACT:

Based mostly on a convex optimization approach, we propose a brand new technique of multi-camera deployment for visual coverage of a three-D object surface. In explicit, the optimal placement of one camera is first formulated as translation and rotation convex optimization issues, respectively, over a group of covered triangle pieces on the target object. The convex optimization is recursively applied to expand the lined area of the one camera, with the initially lined triangle items being chosen along the object boundary for the first trial through a choice criterion. Then, the same optimization procedures are applied to put the next camera and thereafter. It's noticed that our optimization approach guarantees that each camera is placed at the optimal pose in some sense for a cluster of triangles rather than a single piece. This feature, together with the choice criterion for initially covered triangles, reduces the quantity of operating cameras whereas still satisfying varied constraint requirements like resolution, field of read, blur, and occlusion. Both simulation and experimental results are presented to show superior performance of the proposed approach, comparing with the results from different existing ways.