Results 251 to 260 of about 165,702 (282)

3D point clouds parameterization alogrithm

2008 9th International Conference on Signal Processing, 2008
In this paper, we propose a 3D data clouds parameterization algorithm. Genus-zero clouds data are topologically equivalent to a sphere, hence this is the natural parameter domain for them. Firstly, we parameterize a 3D point onto a spherical domain means assigning a 3D position on the unit sphere for each point of the 3D data clouds, this is called a ...
null Lihui Wang, null Baozong Yuan, null Zhenjiang Miao   +2 more
openaire   +1 more source

Guided 3D point cloud filtering

Multimedia Tools and Applications, 2017
3D 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, Jesse S. Jin, Ming-Jie Wang, Wei Jiang   +3 more
openaire   +1 more source

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 Kamberov, Gerda Kamberova, Amit Jain   +2 more
openaire   +1 more source

Structural Relation Modeling of 3D Point Clouds

IEEE Transactions on Image Processing
In this paper, we propose an effective plug-and-play module called structural relation network (SRN) to model structural dependencies in 3D point clouds for feature representation. Existing network architectures such as PointNet++ and RS-CNN capture local structures individually and ignore the inner interactions between different sub-clouds.
Yu Zheng, Jiwen Lu, Yueqi Duan, Jie Zhou
openaire   +2 more sources

3D Point Cloud Analysis

2021
Shan Liu, Min Zhang, Pranav Kadam, C.-C. Jay Kuo   +3 more
openaire   +1 more source

3D hyperspectral point cloud generation

2019
Remote Sensing technologies allow to map biophysical, biochemical, and earth surface parameters of the land surface. Of especial interest for various applications in environmental and urban sciences is the combination of spectral and 3D elevation information.
Brell, Maximilian (Dr.), Segl, Karl (Dr.), Guanter, Luis (Prof. Dr.), Bookhagen, Bodo (Prof. Dr.)   +3 more
openaire   +1 more source

Persistent Point Feature Histograms for 3D Point Clouds

2008
This paper proposes a novel way of characterizing the local geometry of 3D points, using persistent feature histograms. The relationships between the neighbors of a point are analyzed and the resulted values are stored in a 16-bin histogram. The histograms are pose and point cloud density invariant and cope well with noisy datasets.
Rusu Radu Bogdan, Marton Zoltan Csaba, Blodow Nico, Beetz Michael   +3 more
openaire   +1 more source

Transformer for 3D Point Clouds.

IEEE transactions on pattern analysis and machine intelligence
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, Rudrasis, Chakraborty, Stella X, Yu   +2 more
openaire   +1 more source

Cf3d: Category Fused 3d Point Cloud Retrieval

SSRN Electronic Journal, 2022
Zongyi Xu, Ruicheng Zhang, Zuo Li, Shiyang Cheng, Huiyu Zhou, Weisheng Li, Xinbo Gao   +6 more
openaire   +1 more source

Deep Learning for 3D Point Clouds: A Survey

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Yulan Guo, Wang Hanyun, Qingyong Hu
exaly