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RGB-D tracking of complex shapes using coarse object models

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This paper presents a framework for accurately tracking objects of complex shapes with joint minimization of geometric and photometric parameters using a coarse 3D object model with the RGB-D cameras. Tracking with coarse 3D model is remarkably useful for industrial applications. A technique is proposed that uses a combination of point-to-plane distance minimization and photometric error minimization to track objects accurately. The concept of ‘keyframes’ are used in this system of object tracking for minimizing drift. The proposed approach is validated on both simulated and real data. Experimental results show that our approach is more accurate than existing state-of-the-art approaches, especially when dealing with low-textured objects with multiple coplanar faces.
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hal-02129243 , version 1 (14-05-2019)



Agniva Sengupta, Alexandre Krupa, Eric Marchand. RGB-D tracking of complex shapes using coarse object models. ICIP 2019 - IEEE International Conference on Image Processing, Sep 2019, Taipei, Taiwan. pp.1-5, ⟨10.1109/ICIP.2019.8803574⟩. ⟨hal-02129243⟩
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