Colored Point Cloud Registration Revisited

@article{Park2017ColoredPC,
  title={Colored Point Cloud Registration Revisited},
  author={Jaesik Park and Qian-Yi Zhou and Vladlen Koltun},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={143-152}
}
We present an algorithm for aligning two colored point clouds. [...] Key Result The precision of the resulting system is demonstrated on real-world scenes with accurate ground-truth models.Expand
Iterative K-Closest Point Algorithms for Colored Point Cloud Registration
TLDR
Two algorithms are presented to minimize a probabilistic cost based on the color-supported soft matching of points in a point cloud to their K-closest points in the other point cloud, applied to a real-world dataset, providing accurate and visually improved results. Expand
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In this paper, we propose a preprocessing for the ICP algorithm to avoid convergence failures. Using a depth camera with the IMU, the movement of it can be measured. We use it for the pre-adjustmentExpand
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TLDR
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Online frame-to-model pipeline to 3D reconstruction with depth cameras using RGB-D information
  • Thiago Dornelles, C. Jung
  • Computer Science
  • 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)
  • 2020
TLDR
This work presents an online pipeline for incremental 3D reconstruction and 6-DoF camera pose estimation based on colored point clouds captured by consumer RGB-D cameras through an adaptive weighting scheme that avoids eventual misalignment errors between RGB and depth data. Expand
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TLDR
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References

SHOWING 1-10 OF 47 REFERENCES
Registration of colored 3D point clouds with a Kernel-based extension to the normal distributions transform
TLDR
A new algorithm for scan registration of colored 3D point data which is an extension to the normal distributions transform (NDT) by modeling the point distributions as Gaussian mixture-models in color space is presented. Expand
Color supported generalized-ICP
TLDR
It will be shown that the modified algorithm can improve the results without needing any special parameter adjustment, and the additional effort in general does not have an immoderate impact on the runtime, since the number of iterations can be reduced. Expand
Color point cloud registration with 4D ICP algorithm
TLDR
Numerical results on the generated map segments shows that the 4D method resolves ambiguity in registration and converges faster than the 3D ICP. Expand
Dense visual SLAM for RGB-D cameras
TLDR
This paper proposes a dense visual SLAM method for RGB-D cameras that minimizes both the photometric and the depth error over all pixels, and proposes an entropy-based similarity measure for keyframe selection and loop closure detection. Expand
Registration with the Point Cloud Library: A Modular Framework for Aligning in 3-D
TLDR
The PCL incorporates methods for the initial alignment of point clouds using a variety of local shape feature descriptors, as well as methods for refining initial alignments using different variants of the well-known iterative closest point (ICP) algorithm. Expand
A Probabilistic Framework for Color-Based Point Set Registration
TLDR
This paper proposes a probabilistic point set registration framework that exploits available color information associated with the points, based on a model of the joint distribution of 3D-point observations and their color information, while being computationally efficient. Expand
Robust reconstruction of indoor scenes
TLDR
An approach to indoor scene reconstruction from RGB-D video to combine geometric registration of scene fragments with robust global optimization based on line processes that substantially increases the accuracy of reconstructed scene models. Expand
Registration and integration of textured 3D data
TLDR
This work addresses the problem of merging multiple textured 3D data sets, each of which corresponds to a different view of a scene, and shows that the use of color decreases registration error significantly when using omnidirectional stereo data sets. Expand
Color map optimization for 3D reconstruction with consumer depth cameras
TLDR
This work presents a global optimization approach for mapping color images onto geometric reconstructions by optimizing camera poses in tandem with non-rigid correction functions for all images to maximize the photometric consistency of the reconstructed mapping. Expand
Photometric Bundle Adjustment for Dense Multi-view 3D Modeling
TLDR
A dense 3D reconstruction technique that jointly refines the shape and the camera parameters of a scene by minimizing the photometric reprojection error between a generated model and the observed images, hence considering all pixels in the original images is proposed. Expand
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