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The Medial Scaffold of 3D Unorganized Point Clouds

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007
We introduce the notion of the medial scaffold, a hierarchical organization of the medial axis of a 3D shape in the form of a graph constructed from special medial curves connecting special medial points. A key advantage of the scaffold is that it captures the qualitative aspects of shape in a hierarchical and tightly condensed representation.
Frederic F. Leymarie, Benjamin B. Kimia
openaire   +3 more sources

3D Shape from Unorganized 3D Point Clouds

2005
We present a framework to automatically infer topology and geometry from an unorganized 3D point cloud obtained from a 3D scene. If the cloud is not oriented, we use existing methods to orient it prior to recovering the topology. We develop a quality measure for scoring a chosen topology/orientation.
George I. Kamberov   +2 more
openaire   +2 more sources

Registration of Point Clouds for 3D Shape Inspection

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006
Point cloud registration and sensor calibration are two critical technical issues concerning robot-mounted, area sensor systems. Iterative Closest Point (ICP)-based algorithms developed in the past are commonly used for point cloud registration. However, due to its least squared fitting nature, registration quality depends on how closely the measured ...
Quan Shi   +3 more
openaire   +2 more sources

Transformer for 3D Point Clouds.

IEEE transactions on pattern analysis and machine intelligence, 2022
Deep neural networks are widely used for understanding 3D point clouds. At each point convolution layer, features are computed from local neighbourhoods of 3D points and combined for subsequent processing in order to extract semantic information. Existing methods adopt the same individual point neighborhoods throughout the network layers, defined by ...
Jiayun Wang   +2 more
openaire   +2 more sources

SGCNN for 3D Point Cloud Classification

2022 14th International Conference on Machine Learning and Computing (ICMLC), 2022
Shiyun Liu   +3 more
openaire   +1 more source

3DSAINT Representation for 3D Point Clouds

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023
openaire   +1 more source

Deep Learning for 3D Point Clouds: A Survey

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Yulan Guo, li Liu, Mohammed Bennamoun
exaly  

Unsupervised Point Cloud Representation Learning With Deep Neural Networks: A Survey

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
Dayan Guan, Aoran Xiao, Shijian Lu
exaly  

PCT: Point Cloud Transformer

Computational Visual Media, 2021
Zheng-Ning Liu, Shi-Min Hu, Tai-Jiang Mu
exaly  

OctFormer: Octree-Based Transformers for 3D Point Clouds

ACM Transactions on Graphics, 2023
Peng-Shuai Wang
exaly  

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