Colored Point Cloud Registration Revisited

2017 IEEE International Conference on Computer Vision (ICCV)(2017)

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摘要
We present an algorithm for aligning two colored point clouds. The key idea is to optimize a joint photometric and geometric objective that locks the alignment along both the normal direction and the tangent plane. We extend a photometric objective for aligning RGB-D images to point clouds, by locally parameterizing the point cloud with a virtual camera. Experiments demonstrate that our algorithm is more accurate and more robust than prior point cloud registration algorithms, including those that utilize color information. We use the presented algorithms to enhance a state-of-the-art scene reconstruction system. The precision of the resulting system is demonstrated on real-world scenes with accurate ground-truth models.
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关键词
tangent plane,prior point cloud registration algorithms,color information,geometric objective,colored point cloud registration,RGB-D images aligning,state-of-the-art scene reconstruction system,photometric objective optimization
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