A sensor-based solution to the "next best view" problem

Acquiring the complete surface geometry of an object using a range scanner invariably requires that multiple range images be taken of it from different viewpoints. An algorithm is presented which solves the “next best view” (NBV) problem: determine the next position for the range scanner given its previous scans of the object. As part of a complete surface acquisition system the scanner’s next position should cause it not only to sample more of the object’s surface but to resample part of the object already scanned to allow for the registration and integration of the new data with the previous scans. A novel representation, positional space, is presented which facilitates a solution to the NBV problem by representing what must be and what can be scanned in a unified data structure. The expensive operation of determining the visibility of part of the viewing volume is computed only once, not for each potential position of the scanner, thus breaking the computational burden of choosing the NBV from a large number of positions. No assumptions are made about the geometry or topology of the object. The algorithm is self-terminating, will scan all visible surfaces of an object and can be directed to resample surfaces which were scanned with low confidence. In addition, the algorithm will work with nearly any range camera and scanning setup. A completely automated surface acquisition system featuring the proposed NBV algorithm is demonstrated on a