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A Hybrid 2D-3D RGB-D Method for Growth Axis Estimation and Robotic Grasp Pose Generation of Phalaenopsis Orchid Buds. [PDF]
MethodsXNguyen TD +6 more
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SDA-Reg: large-scale dynamic scene point cloud registration with semantic dual-stream attention. [PDF]
Sci RepFu S, Cai Q, Yao Z, Chen Q, Lin T.
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Efficient and lightweight long-range modeling for 3d point cloud classification and segmentation. [PDF]
PLoS OneLiu D, Deng Y, Zou J, Fan S.
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Editorial on "Application of LiDAR Remote Sensing and Mapping". [PDF]
Sensors (Basel)Zhu X, Nie S, Wang C.
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SEGMENTATION OF PLANT POINT CLOUDS FOR PHENOTYPING
2023 31st Signal Processing and Communications Applications Conference (SIU), 2023In this paper, we consider semantic segmentation of 3D plant point clouds. We propose various modifications to improve the performance of two main state-of-the-art methods for semantic segmentation of plants. In the first method, we consider the classical machine learning approach where local geometric features are classified via SVM.
Yavuz, Ahmetcan +3 more
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Semantic Segmentation on Radar Point Clouds
2018 21st International Conference on Information Fusion (FUSION), 2018Semantic segmentation on radar point clouds is a new challenging task in radar data processing. We demonstrate how this task can be performed and provide results on a large data set of manually labeled radar reflections. In contrast to previous approaches where generated feature vectors from clustered reflections were used as an input for a classifier,
Ole Schumann +3 more
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On the segmentation of 3D LIDAR point clouds
2011 IEEE International Conference on Robotics and Automation, 2011This paper presents a set of segmentation methods for various types of 3D point clouds. Segmentation of dense 3D data (e.g. Riegl scans) is optimised via a simple yet efficient voxelisation of the space. Prior ground extraction is empirically shown to significantly improve segmentation performance. Segmentation of sparse 3D data (e.g.
Bertrand Douillard +6 more
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3D point cloud segmentation: A survey
2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM), 20133D point cloud segmentation is the process of classifying point clouds into multiple homogeneous regions, the points in the same region will have the same properties. The segmentation is challenging because of high redundancy, uneven sampling density, and lack explicit structure of point cloud data.
Anh Nguyen 0003, Bac Le
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TLS point cloud segmentation based on points features
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017This article proposes a point cloud segmentation method by merely relying on the spatial and echo characteristics of the point cloud of the terrestrial laser scanning (TLS). Firstly, terrain point cloud and off-terrain point cloud will be separated according to their own spatial characteristics. Then further segmentation to the terrain point cloud part
Hongbo Jiang 0003, Qisong Jiao
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Interactive Learning for Point‐Cloud Motion Segmentation
Computer Graphics Forum, 2013AbstractSegmenting a moving foreground (fg) from its background (bg) is a fundamental step in many Machine Vision and Computer Graphics applications. Nevertheless, hardly any attempts have been made to tackle this problem in dynamic 3D scanned scenes. Scanned dynamic scenes are typically challenging due to noise and large missing parts.
Yerry Sofer, Tal Hassner, Andrei Sharf
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