Y. Lu and S. Smith (USA)
3D recovery, Stereo match, Computer modeling, Wide baseline
Recovering 3D objects from 2D photos is an important application in the areas of computer vision, computer intelligence, feature recognition, and virtual reality. This paper describes an innovative and systematic method to integrate automatic feature extraction, automatic feature matching, manual revision, feature recovery, and model reconstruction as an effective recovery tool. This method has been proven to be a convenient and inexpensive way to recover 3D scenes and models directly from 2D photos. We have developed a new automatic key point selection and hierarchical matching algorithm for matching 2D photos, which have less similarity. Our method uses a universal camera intrinsic matrix estimation method to omit camera calibration experiment. We have also developed a new automatic texture-mapping algorithm to find the best textures from 2D photos. In this paper, we include some examples and results to show the capability of the developed tool.
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