Planning of optimal trajectories for optical 3D sensors by means of tensor voting

Camera positioning in vision applications is challenging, but of crucial importance. This is definitely the case when the goal is to make a 3D scan. This is because camera positions determine which parts of an object are visible and which measuring accuracy will be achieved. Our ambition is to automatically determine the scan path or positions of the camera during a 3D scan for a known object. To solve this engineering problem we will use mathematical techniques as 'tensor voting' and 'surface fitting'. The final algorithm provides the industry with the following advantages:1. Faster and more efficient 3D scans2. More complicated objects can be scanned3. Automatic scan planning for every type of 3D sensor/camera in one model.4. Automatic scan planning for specific measurement setups currently used in industry. This reduces the need for expensive experts.

Keywords:3D SCANNING, COMPUTER VISION

Disciplines:Analysis, Applied mathematics in specific fields, General mathematics, History and foundations, Other mathematical sciences and statistics, Astronomy and space sciences, Condensed matter physics and nanophysics