Recursive model optimization using ICP and free moving 3D data acquisition

We describe a recursive multiresolution algorithm that reconstructs high-resolution and high-accuracy 3D images from low-resolution sparse range images or profiles. The method starts by creating a rough, partial, and potentially distorted estimate of the model of the object from an initial subset of sparse range data; then, using ICP algorithms, it recursively improves and refines the model by adding new range information. In parallel, real-time tracking of the object is performed in order to allow the laser scan to be automatically centered on the object. The end result is the creation of a high-resolution and accurate 3D model of a free-floating object, and real-time tracking of its position. Examples of the method are presented when the object and the 3D camera are moving freely with respect to each other. The system provides high accuracy hand-held laser scanning that does not require complex and costly mechanical scanning apparatus or external positioning devices.