Results 61 to 70 of about 22,647 (298)
Point cloud segmentation for urban scene classification [PDF]
, 2013 High density point clouds of urban scenes are used to identify object classes like buildings, vegetation, vehicles, ground, and water. Point cloud segmentation can support classification and further feature extraction provided that the segments are ...
Vosselman, G.; id_orcid +2 more
core +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe 3-D point cloud semantic segmentation extends the development of computer vision. Accurate point cloud semantic segmentation is a fundamental problem in point cloud applications.
Zhiwen Zhang +3 more
doaj +1 more source
Graph cut based point-cloud segmentation for polygonal reconstruction [PDF]
, 2009 . The reconstruction of 3D objects from a point-cloud is based on sufficient separation of the points representing objects of interest from the points of other, unwanted objects. This operation called segmentation is discussed in this paper.
Jiri Zara, David Sedlacek
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PointAF: A Novel Semantic Segmentation Network for Point Cloud [PDF]
, 2023 Point cloud semantic segmentation is a crucial problem in computer vision, which aims to assign semantic labels to each point in a point cloud. However, the sparsity and irregularity of point cloud data pose significant challenges to achieving accurate ...
Chen, Tianze +4 more
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DTNLS: 3D Point Cloud Segmentation Based on 2D Image and 3D Point Cloud Double Texture Feature
IEEE AccessPanoramic segmentation of 3D point clouds is an essential and challenging technology for robots with 3D detection and measurement capabilities. In order to fuse the color information of 2D image pixels with the spatial position information of the 3D ...
Zhiguang Liu +5 more
doaj +1 more source
Associatively Segmenting Instances and Semantics in Point Clouds [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 A 3D point cloud describes the real scene precisely and intuitively.To date how to segment diversified elements in such an informative 3D scene is rarely discussed. In this paper, we first introduce a simple and flexible framework to segment instances and semantics in point clouds simultaneously. Then, we propose two approaches which make the two tasks
Xinlong Wang +4 more
openaire +2 more sources
SoftGroup for 3D Instance Segmentation on Point Clouds
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 To appear in CVPR ...
Thang Vu +4 more
openaire +2 more sources
Molecular Oncology, EarlyView.Here, we demonstrate that HS1BP3 interacts with Cortactin through a proline‐rich region (PRR3.1) and show that this interaction, and HS1BP3 itself, promote cancer cell proliferation and invasion. Inhibition of this interaction leads to build‐up of TKS5 in multivesicular endosomes and altered secretion of CD63 and CD9, providing an explanation for the ...
Arja Arnesen Løchen +9 more
wiley +1 more source
IEEE AccessIntelligent inspection has become an important trend in the development of substation operation and maintenance technology, and fast and accurate point cloud segmentation of the large amount of point cloud data collected in the process of intelligent ...
Ze Zhang +5 more
doaj +1 more source
SEGCloud: Semantic Segmentation of 3D Point Clouds [PDF]
2017 International Conference on 3D Vision (3DV), 2017 3D semantic scene labeling is fundamental to agents operating in the real world. In particular, labeling raw 3D point sets from sensors provides fine-grained semantics. Recent works leverage the capabilities of Neural Networks (NNs), but are limited to coarse voxel predictions and do not explicitly enforce global consistency.
Lyne P. Tchapmi +4 more
openaire +2 more sources