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Guided 3D point cloud filtering
Multimedia Tools and Applications, 20173D point cloud has gained significant attention in recent years. However, raw point clouds captured by 3D sensors are unavoidably contaminated with noise resulting in detrimental efforts on the practical applications. Although many widely used point cloud filters such as normal-based bilateral filter, can produce results as expected, they require a ...
Xian-Feng Han +3 more
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3D point cloud segmentation: A survey
2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM), 20133D point cloud segmentation is the process of classifying point clouds into multiple homogeneous regions, the points in the same region will have the same properties. The segmentation is challenging because of high redundancy, uneven sampling density, and lack explicit structure of point cloud data.
Anh Nguyen 0003, Bac Le
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The Medial Scaffold of 3D Unorganized Point Clouds
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007We 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
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Transformer for 3D Point Clouds.
IEEE transactions on pattern analysis and machine intelligence, 2022Deep 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
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3D Shape from Unorganized 3D Point Clouds
2005We 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
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Registration of Point Clouds for 3D Shape Inspection
2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006Point 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
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SGCNN for 3D Point Cloud Classification
2022 14th International Conference on Machine Learning and Computing (ICMLC), 2022Shiyun Liu +3 more
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3DSAINT Representation for 3D Point Clouds
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023openaire +1 more source
Unsupervised Point Cloud Representation Learning With Deep Neural Networks: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Dayan Guan, Aoran Xiao, Shijian Lu
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