Fused Projection-Based Point Cloud Segmentation [PDF]
Sensors, 2022 Semantic segmentation is used to enable a computer to understand its surrounding environment. In image processing, images are partitioned into segments for this purpose.
Maximilian Kellner +2 more
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Scattered Train Bolt Point Cloud Segmentation Based on Hierarchical Multi-Scale Feature Learning [PDF]
Sensors, 2023 In view of the difficulty of using raw 3D point clouds for component detection in the railway field, this paper designs a point cloud segmentation model based on deep learning together with a point cloud preprocessing mechanism.
Ni Zeng +4 more
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PlantEFRSegnet: A Plant Point Cloud Segmentation Network Based on Edge Point Preservation and Feature Feedback Repair [PDF]
SensorsThe segmentation of 3D point clouds of plant organs, such as leaves and stems, helps to monitor plant growth and is a key step in plant growth phenotype analysis.
Bin Li, Peng Liu, Yonghan Zhang
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MASPC_Transform: A Plant Point Cloud Segmentation Network Based on Multi-Head Attention Separation and Position Code [PDF]
Sensors, 2022 Plant point cloud segmentation is an important step in 3D plant phenotype research. Because the stems, leaves, flowers, and other organs of plants are often intertwined and small in size, this makes plant point cloud segmentation more challenging than ...
Bin Li, Chenhua Guo
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Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage: A Comprehensive Review
Remote Sensing, 2023 In the cultural heritage field, point clouds, as important raw data of geomatics, are not only three-dimensional (3D) spatial presentations of 3D objects but they also have the potential to gradually advance towards an intelligent data structure with ...
Su Yang, Miaole Hou, Songnian Li
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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) based feature selection and classification, and (iv) post-processing.
Xiangguo Lin
exaly +3 more sources
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Developing a robust point cloud segmentation algorithm for individual trees from an amount of point cloud data has great significance for tracking tree changes.
Xiaoyu Hu, Dan Li
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A Review of Deep Learning-Based Semantic Segmentation for Point Cloud
IEEE Access, 2019 In recent years, the popularity of depth sensors and 3D scanners has led to a rapid development of 3D point clouds. Semantic segmentation of point cloud, as a key step in understanding 3D scenes, has attracted extensive attention of researchers.
Jiaying Zhang +3 more
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Comprehensive review on 3D point cloud segmentation in plants
Artificial Intelligence in AgricultureSegmentation of three-dimensional (3D) point clouds is fundamental in comprehending unstructured structural and morphological data. It plays a critical role in research related to plant phenomics, 3D plant modeling, and functional-structural plant ...
Hongli Song +3 more
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Segmentation of Points in the Future: Joint Segmentation and Prediction of a Point Cloud [PDF]
IEEE Access, 2021 Recognizing and predicting future three-dimensional (3D) scenes are crucial steps for real-time vision-based control systems, as these steps enable them to react appropriately in advance. In this study, a method for predicting the position of a 3D point cloud in the future and simultaneously segmenting the predicted point cloud is proposed for the ...
Cheng Wencan, Jong Hwan Ko
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