Stereo imaging with uncalibrated camera

3D images provide more information to human than their 2D counterparts and have many applications in entertainment, scientific data visualization, etc. The ability to generate accurate 3D dynamic scene and 3D movie from uncalibrated cameras is a challenge. We propose a systematic approach to stereo image/video generation. With our proposed approach, a realistic 3D scene can be created via either a single uncalibrated moving camera or two synchronized cameras. 3D video can also be generated through multiple synchronized video streams. Our approach first uses a Gabor filter bank to extract image features. Second, we develop an improved Elastic Graph Matching method to perform reliable image registration from multi-view images or video frames. Third, a fast and efficient image rectification method based on multi-view geometry is presented to create stereo image pairs. Extensive tests using real images collected from widely separated cameras were performed to test our proposed approach.