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Point pattern matching for augmented reality

Liming Yang 1
1 CRENAU - Centre de recherche nantais Architectures Urbanités
AAU - Ambiances, Architectures, Urbanités
Abstract : Registration is a very important task in Augmented Reality (AR). It provides the spatial alignment between the real environment and virtual objects. Unlike tracking (which relies on previous frame information), wide baseline localization finds the correct solution from a wide search space, so as to overcome the initialization or tracking failure problems. Nowadays, various wide baseline localization methods have been applied successfully. But for objects with no or little texture, there is still no promising method. One possible solution is to rely on the geometric information, which sometimes does not vary as much as texture or color. This dissertation focuses on new wide baseline localization methods entirely based on geometric information, and more specifically on points. I propose two novel point pattern matching algorithms, RRDM and LGC. Especially, LGC registers 2D or 3D point patterns under any known transformation type and supports multipattern recognitions. It has a linear behavior with respect to the number of points, which allows for real-time tracking. It is applied to multi targets tracking and augmentation, as well as to 3D model registration. A practical method for projector-camera system calibration based on LGC is also proposed. It can be useful for large scale Spatial Augmented Reality (SAR). Besides, I also developed a method to estimate the rotation axis of surface of revolution quickly and precisely on 3D data. It is integrated in a novel framework to reconstruct the surface of revolution on dense SLAM in real-time.
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Liming Yang. Point pattern matching for augmented reality. Optics / Photonic. École centrale de Nantes, 2016. English. ⟨NNT : 2016ECDN0025⟩. ⟨tel-02990905⟩

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