An automatic method for solving the problem of view planning in high-resolution industrial inspection is presented. The method's goal is to maximize the visual coverage, and to minimize the number of cameras used for inspection. Using a CAD model of the object of interest, we define the scene-points and the viewpoints, with the later being the solution space. The problem formulation accurately encapsulates all the vision- and task-related requirements of the design process for inspection systems. We use a graph-based approach to formulate a solution for the problem. The solution is implemented as a greedy algorithm, and the method is validated through experiments.

We present a method for automatic deployment of visual sensor networks, based on a polygonal mesh model of the task. This method uses a graph-based approach to ensure an optimal level of visual overlap between the sensors. In this brief our method is further leveraged by increasing the size of the solution space, which in turn moves the solution closer to the optimal state. The increase in computational cost incurred by the extended solution space is handled by taking advantage of some occlusion properties of a convex partitioning of the task. Simulations are used to demonstrate the effectiveness of the approach.