Results 11 to 20 of about 997,464 (307)

Adaptive Clustering for Point Cloud

Sensors
The point cloud segmentation method plays an important role in practical applications, such as remote sensing, mobile robots, and 3D modeling. However, there are still some limitations to the current point cloud data segmentation method when applied to ...
Zitao Lin, Chuanli Kang, Siyi Wu, Xuanhao Li, Lei Cai, Dan Zhang, Shiwei Wang   +6 more
doaj   +3 more sources

Classification of ALS Point Cloud with Improved Point Cloud Segmentation and Random Forests [PDF]

Remote Sensing, 2017
This paper presents an automated and effective framework for classifying airborne laser scanning (ALS) point clouds. The framework is composed of four stages: (i) step-wise point cloud segmentation, (ii) feature extraction, (iii) Random Forests (RF ...
Huan Ni, Xiangguo Lin, Jixian Zhang
doaj   +3 more sources

PCT: Point cloud transformer [PDF]

Computational Visual Media, 2021
The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing. This paper presents a novel framework named Point Cloud Transformer(PCT) for point cloud learning. PCT is based on Transformer, which achieves huge success in natural language processing and displays great potential in image ...
Meng-Hao Guo, Zheng-Ning Liu, Tai-Jiang Mu, Ralph R. Martin, Jun-Xiong Cai, Shi-Min Hu   +5 more
openaire   +5 more sources

Georeferenced Point Clouds: A Survey of Features and Point Cloud Management [PDF]

ISPRS International Journal of Geo-Information, 2013
This paper presents a survey of georeferenced point clouds. Concentration is, on the one hand, put on features, which originate in the measurement process themselves, and features derived by processing the point cloud. On the other hand, approaches for the processing of georeferenced point clouds are reviewed.
Johannes Otepka, Sajid Ghuffar, Christoph Waldhauser, Ronald Hochreiter, Norbert Pfeifer   +4 more
openaire   +5 more sources

Geodesics on Point Clouds [PDF]

Mathematical Problems in Engineering, 2014
We present a novel framework to compute geodesics on implicit surfaces and point clouds. Our framework consists of three parts, particle based approximate geodesics on implicit surfaces, Cartesian grid based approximate geodesics on point clouds, and geodesic correction.
Hongchuan Yu, Jian J. Zhang, Zheng Jiao
openaire   +2 more sources

Picking Towels in Point Clouds [PDF]

Sensors, 2019
Picking clothing has always been a great challenge in laundry or textile industry automation, especially when some clothes are of the same colors, material and entangled with each other. In order to solve the problem, we present a grasp pose determination method to pick towels placed in a laundry basket or on a table. In our method, it is not needed to
Wang, Xiaoman, Jiang, Xin, Zhao, Jie, Wang, Shengfan, Yang, Tao, Liu, Yunhui   +5 more
openaire   +3 more sources

Topological Point Cloud Clustering

Proceedings of the 40th International Conference on Machine Learning. International Conference on Machine Learning, ICML 2023, Honolulu, USA, 2023
Accepted at the 40th International Conference on Machine Learning (ICML), 2023.
Grande, Vincent P., Schaub, Michael T.
openaire   +3 more sources

PointMixup: Augmentation for Point Clouds [PDF]

, 2020
This paper introduces data augmentation for point clouds by interpolation between examples. Data augmentation by interpolation has shown to be a simple and effective approach in the image domain. Such a mixup is however not directly transferable to point clouds, as we do not have a one-to-one correspondence between the points of two different objects ...
Chen, Y., Hu, V.T., Gavves, E., Mensink, T., Mettes, P., Yang, P., Snoek, C.G.M.   +6 more
openaire   +5 more sources

DPDist: Comparing Point Clouds Using Deep Point Cloud Distance [PDF]

, 2020
We introduce a new deep learning method for point cloud comparison. Our approach, named Deep Point Cloud Distance (DPDist), measures the distance between the points in one cloud and the estimated surface from which the other point cloud is sampled. The surface is estimated locally and efficiently using the 3D modified Fisher vector representation.
Yizhak Ben-Shabat, Dahlia Urbach, Michael Lindenbaum   +2 more
openaire   +4 more sources

POINT CLOUD SERVER (PCS) : POINT CLOUDS IN-BASE MANAGEMENT AND PROCESSING [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
Abstract. In addition to the traditional Geographic Information System (GIS) data such as images and vectors, point cloud data has become more available. It is appreciated for its precision and true three-Dimensional (3D) nature. However, managing the point cloud can be difficult due to scaling problems and specificities of this data type.
Nicolas Paparoditis, Julien Perret, Rémi Cura   +2 more
openaire   +4 more sources