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Coarse-fine point cloud registration based on local point-pair features and the iterative closest point algorithm
3D point cloud registration has a wide range of applications in object shape detection, robot navigation and 3D reconstruction. Aiming at the...
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SPROSAC: Streamlined progressive sample consensus for coarse–fine point cloud registration
With the development of 3D matching technology, point cloud registration (PCR) based on corresponding points has received increasing attention in the...
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Point cloud registration with quantile assignment
Point cloud registration is a fundamental problem in computer vision. The problem encompasses critical tasks such as feature estimation,...
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A fast coarse-to-fine point cloud registration based on optical flow for autonomous vehicles
Point cloud registration is a vital prerequisite for many autonomous vehicle tasks. However, balancing the accuracy and computational complexity is...
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Local feature guidance framework for robust 3D point cloud registration
3D point cloud registration is a basic task in computer vision. In recent years, various of learning-based methods have been proposed to solve this...
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Coarse registration of point cloud base on deep local extremum detection and attentive description
Coarse registration of point cloud is a necessary step for object digitization. However, insufficient overlap**, large pose difference and the...
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Fast Point Cloud Registration for Urban Scenes via Pillar-Point Representation
Efficient and robust point cloud registration is an essential task for real-time applications in urban scenes. Most methods introduce keypoint...
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TopFormer: Topology-Aware Transformer for Point Cloud Registration
The extraction of robust feature descriptors is crucial for achieving accurate point cloud registration. While the attention mechanism plays an...
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Low-overlap point cloud registration algorithm based on coupled iteration
We present BC-PCNet, a P oint C loud registration model based on B idirectional C oupled iteration. The proposed model addresses the challenge of...
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Registration of Structured Light Camera Point Cloud Data with CT Images
With the advancement of structured-light cameras, surgical robots equipped with such cameras have been utilized for lesion localization during...
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Point Cloud Registration Network Based on Convolution Fusion and Attention Mechanism
In 3D vision, point cloud registration remains a major challenge, especially in end-to-end deep learning, where low-quality point pairs will directly...
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3D Point Cloud Registration Method Based on Structural Matching of Feature Points
3D point cloud is an important expression of three-dimensional environment information. The registration of point cloud is the basis of realizing the...
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Adaptive ICP Registration Algorithm Based on the Neighborhood of SIFT Feature Points
The ICP algorithm has been widely used for point cloud registration, but it has low computational efficiency under large-scale point cloud data....
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SingleMatch: a point cloud coarse registration method with single match point and deep-learning describer
Point cloud registration is a necessary step of object digitization. In this paper, we propose a coarse registration method with a single match...
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A noval weighted distance and local density double histogram used in 3D local feature description
In the field of computer vision, it is a challenging task to accurately describe local features in point clouds with different noise, resolution and...
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PuzzleNet: Boundary-Aware Feature Matching for Non-Overlap** 3D Point Clouds Assembly
We address the 3D shape assembly of multiple geometric pieces without overlaps, a scenario often encountered in 3D shape design, field archeology,...
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Retrieval-and-alignment based large-scale indoor point cloud semantic segmentation
Current methods for point cloud semantic segmentation depend on the extraction of descriptive features. However, unlike images, point clouds are...
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6DOF pose estimation of a 3D rigid object based on edge-enhanced point pair features
The point pair feature (PPF) is widely used for 6D pose estimation. In this paper, we propose an efficient 6D pose estimation method based on the PPF...
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Addressing the generalization of 3D registration methods with a featureless baseline and an unbiased benchmark
Recent 3D registration methods are mostly learning-based that either find correspondences in feature space and match them, or directly estimate the...
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Automatic multi-view registration of point clouds via a high-quality descriptor and a novel 3D transformation estimation technique
Generally, performing multiple scans is necessary to cover entire scanning area, and multiple point clouds are thus obtained. These point clouds need...
