Automatic coarse registration of three-dimensional surfaces by information theoretic selection of salient points

We describe a new method to register surface data measured by optical three-dimensional (3-D) sensors from various views of an object. With our method, complete 3-D models of objects can be generated without user interaction. Circumferential acquisition of 3-D objects is done by taking several views from different directions. To generate a complete 3-D-model, the views must be aligned with each other. This process is called registration and is commonly done interactively by searching for so-called corresponding points in the different views and by use of these points to calculate the appropriate rotation and translation. Our approach is based on automatically finding points that are eye catching or salient compared with other surface points. We derive a quantitative measure of point salience and a feature definition for free-form surfaces by introducing a concept to measure pragmatic information. Experiments confirm that our salient points can be robustly located on general free-form surfaces, even if there are no corners or edges. Furthermore, the neighborhoods of the salient points are highly distinguishable from each other. This results in a large reduction of the complexity of the subsequent geometric matching. The computing time is only a few seconds. We present results from various fields of application.