Prior-based facade rectification for AR in urban environment

Antoine Fond 1 Marie-Odile Berger 1 Gilles Simon 1
1 MAGRIT - Visual Augmentation of Complex Environments
Inria Nancy - Grand Est, LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
Abstract : We present a method for automatic facade rectification and detection in the Manhattan world scenario. A Bayesian inference approach is proposed to recover the Manhattan directions in camera coordinate system, based on a prior we derived from the analysis of urban datasets. In addition, a SVM-based procedure is used to identify right-angle corners in the rectified images. These corners are clustered in facade regions using a greedy rectangular min-cut technique. Experiments on a standard dataset show that our algorithm performs better or as well as state-of-the-art techniques while being much faster.
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Communication dans un congrès
ISMAR workshop on Urban Augmented Reality, Sep 2015, Fukuoka, Japan
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Antoine Fond, Marie-Odile Berger, Gilles Simon. Prior-based facade rectification for AR in urban environment. ISMAR workshop on Urban Augmented Reality, Sep 2015, Fukuoka, Japan. 〈hal-01235842〉

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