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Published byRose Carson Modified over 8 years ago
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Yannick FranckenChris HermansPhilippe Bekaert Hasselt University – tUL – IBBT Expertise Centre for Digital Media, Belgium {firstname.lastname}@uhasselt.be
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Goal Geometric calibration of a camera w.r.t. a screen
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Vision based HCI 3D reconstruction Motivation [Chen et al., SPIE 2002][Gorodnichy et al., SPIE 2002] [Francken et al., CVPR 2008][Nehab et al., CVPR 2008]
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Planar mirror Related Work [Funk and Yang, CRV 2007] [Bonfort et al., ACCV 2006]
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Planar mirror Spherical mirror –Corner reflections Related Work [Tarini et al., Graphical Models 2005]
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Planar mirror Spherical mirror –Corner reflections –Edge reflections Related Work [Francken et al., CRV 2007]
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Planar mirror Spherical mirror –Corner reflections –Edge reflections –Surface reflection Increased accuracy Less manual interventions Robust screen reflection detection Our Approach
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Concept 1.Mirror detection 2.Screen pixel labeling 3.3D reconstruction
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Mirror detection 1.Internal camera parameters K 2.Background subtraction 3.Edge extraction 4.Ellipse fitting 5.2D ellipse to 3D sphere
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Screen pixel labeling
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Reflection mask
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3D reconstruction Reflected ray intersections Plane estimation Grid estimation Known parameters:
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Reflected ray intersections Plane estimation Grid estimation Result: 2D pixel u 3D location x x = M. u 3D reconstruction Solution: Find 2D – 2D similarity transform
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Overview x = M. u
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Error as function of pattern refinement Results Accuracy –Ground truth –[Francken et al., CRV 2007] –Our approach
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Error as function of sphere combinations Results
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Error as function of sphere combinations Results
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Error as function of sphere combinations Results
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Error as function of sphere combinations Results
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Screen-camera calibration using Gray codes –Increased accuracy –Less manual interventions –Robust screen reflection detection Conclusion
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Gradient patterns –Speed! –Quality? Camera defocus –Which patterns are robust? Future Work
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Questions? yannick.francken@uhasselt.behttp://research.edm.uhasselt.be/~yfrancken x = M. u
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