Modeling arbitrary objects based on geometric surface conformity

We address the problem of efficient and flexible modeling of arbitrary three-dimensional (3-D) objects and the accurate tracking of the generated model. These goals are reached by combining available multiview image analysis tools with a straightforward 3-D modeling method, which exploit well-established techniques from both computer vision and computer graphics, improving and combining them with new strategies. The basic idea of the technique presented is to use feature points and relevant edges in the images as nodes and edges of an initial two-dimensional wire grid. The method is adaptive in the sense that an initial rough surface approximation is progressively refined at the locations where the triangular patches do not approximate the surface accurately. The approximation error is measured according to the distance of the model to the object surface, taking into account the reliability of the depth estimated from the stereo image analysis. Once the initial wireframe is available, it is deformed and updated from frame to frame according to the motion of the object points chosen to be nodes. At the end of this process we obtain a temporally consistent 3-D model, which accurately approximates the visible object surface and reflects the physical characteristics of the surface with as few planar patches as possible. The performance of the presented methods is confirmed by several computer experiments