Automatic Reconstruction of 3 - D StationaryObjects from Multiple Uncalibrated Camera

A system for the automatic reconstruction of real world objects from multiple uncalibrated camera views is presented. The camera position and orientation for all views, the 3-D shape of the rigid object as well as the associated color information are recovered from the image sequence. The system proceeds in four steps. First, the internal camera parameters describing the imaging geometry are calibrated using a reference object. Second, an initial 3-D description of the object is computed from two views. This model information is then used in a third step to estimate the camera positions for all available views using a novel linear 3-D motion and shape estimation algorithm. The main feature of this third step is the simultaneous estimation of 3-D camera motion parameters and object shape reenement with respect to the initial 3-D model. The initial 3-D shape model exhibits only a few degrees of freedom and the object shape reenement is deened as exible deformation of the initial shape model. Our formulation of the shape deformation allows the object texture to slide on the surface, which diiers from traditional exible body modeling. This novel combined shape and motion estimation using sliding texture considerably improves the calibration data of the individual views in comparison to xed-shape model-based camera motion estimation. Since the shape model used for model-based camera motion estimation is only approximate, a volumetric 3-D reconstruction process is initiated in the fourth step that combines the information from all views simultaneously. The recovered object consists of a set of voxels with associated color information that describes even ne structures and details of the object. New views of the object can be rendered from the recovered 3-D model, which has potential applications in virtual reality or multimedia systems and the emerging eld of video coding using 3-D scene models.