New dynamic zoom calibration technique for a stereo-vision-based multiview 3D modeling system

Abstract

A new technique is proposed for calibrating a 3D modeling system with variable zoom based on multi-view stereo image analysis. The 3D modeling system uses a stereo camera with variable zoom setting and a turntable for rotating an object. Given an object whose complete 3D model (mesh and texture-map) needs to be generated, the object is placed on the turntable and stereo images of the object are captured from multiple views by rotating the turntable. Partial 3D models generated from different views are integrated to obtain a complete 3D model of the object. Changing the zoom to accommodate objects of different sizes and at different distances from the stereo camera changes several internal camera parameters such as focal length and image center. Also, the parameters of the rotation axis of the turntable changes. We present camera calibration techniques for estimating the camera parameters and the rotation axis for different zoom settings. The Perspective Projection Matrices (PPM) of the cameras are calibrated at a selected set of zoom settings. The PPM is decomposed into intrinsic parameters, orientation angles, and translation vectors. Camera parameters at an arbitrary intermediate zoom setting are estimated from the nearest calibrated zoom positions through interpolation. A performance evaluation of this technique is presented with experimental results. We also present a refinement technique for stereo rectification that improves partial shape recovery. And the rotation axis of multi-view at different zoom setting is estimated without further calibration. Complete 3D models obtained with our techniques are presented.