Patchwork++: Fast and Robust Ground Segmentation Solving Partial Under-Segmentation Using 3D Point Cloud [PDF]
IEEE/RJS International Conference on Intelligent RObots and Systems, 2022 In the field of 3D perception using 3D LiDAR sensors, ground segmentation is an essential task for various purposes, such as traversable area detection and object recognition.
Seungjae Lee, Hyungtae Lim, H. Myung
semanticscholar +1 more source
3D image segmentation supported by a point cloud
Discrete and Continuous Dynamical Systems - S, 2021 In this paper, we deal with the 3D image segmentation where the segmented surface is reconstructed by using 3D point cloud data and 3D digital image information. For this task, we apply a mathematical model and numerical method based on the so-called level set algorithm. This method solves surface reconstruction by the application of advection equation
Kósa, Balázs +5 more
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INDOOR 3D POINT CLOUDS SEMANTIC SEGMENTATION BASES ON MODIFIED POINTNET NETWORK [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Indoor 3D point clouds semantics segmentation is one of the key technologies of constructing 3D indoor models,which play an important role on domains like indoor navigation and positioning,intelligent city, intelligent robot etc.
J. Zhao +6 more
doaj +1 more source
Rethinking Design and Evaluation of 3D Point Cloud Segmentation Models
Remote Sensing, 2022 Currently, the use of 3D point clouds is rapidly increasing in many engineering fields, such as geoscience and manufacturing. Various studies have developed intelligent segmentation models providing accurate results, while only a few of them provide ...
Thanasis Zoumpekas +2 more
semanticscholar +1 more source
ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic Convolution [PDF]
Computer Vision and Pattern Recognition, 2023 Existing 3D instance segmentation methods are predominated by the bottom-up design - manually fine-tuned algorithm to group points into clusters followed by a refinement network.
T.D. Ngo +2 more
semanticscholar +1 more source
Leaves Segmentation in 3D Point Cloud [PDF]
, 2017 This paper presents a 3D plant segmentation method with an emphasis on segmentation of the leaves. This method is part of a 3D plant phenotyping project with a main objective that deals with the development of the leaf area over time. First, a 3D point cloud of a plant is obtained with Structure from Motion technique and the cloud is then segmented ...
Gélard, William +6 more
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An Indoor Point Cloud Segmentation Method Fusing with Multi-feature Cluster Ensemble [PDF]
Jisuanji gongcheng, 2018 Aiming at the problem that the traditional point cloud segmentation algorithm is not precise and feature description is not comprehensive in specific scenes,an Affinity Propagation(AP) clustering ensemble segmentation method fusing with 2D and 3D ...
ZENG Bi,HUANG Wen
doaj +1 more source
SEMANTIC SEGMENTATION FOR BUILDING FAÇADE 3D POINT CLOUD FROM 2D ORTHOPHOTO IMAGES USING TRANSFER LEARNING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 The task of semantic segmentation is an important one in the context of 3D building modelling. Indeed, developments in 3D generation techniques have rendered the point cloud ubiquitous.
A. Murtiyoso +4 more
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APPLICATION OF A SHELLNET BASED APPROACH TO SEMANTIC SEGMENTATION IN URBAN POINT CLOUD [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 In recent years, the popularity of airborne, vehicle-borne, and terrestrial 3D laser scanners has driven the rapid development of 3D point cloud processing methods.
D. Chen, X. Ma, X. Lu, J. Xiao
doaj +1 more source
2D-3D Interlaced Transformer for Point Cloud Segmentation with Scene-Level Supervision [PDF]
IEEE International Conference on Computer Vision, 2023 We present a Multimodal Interlaced Transformer (MIT) that jointly considers 2D and 3D data for weakly supervised point cloud segmentation. Research studies have shown that 2D and 3D features are complementary for point cloud segmentation.
Cheng-Kun Yang +3 more
semanticscholar +1 more source