Proceedings ArticleDOI
3D point cloud segmentation: A survey
Anh Nguyen,Bac Le +1 more
- pp 225-230
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TLDR
This survey examines methods that have been proposed to segment 3D point clouds into multiple homogeneous regions and outlines the promising future research directions.Abstract:
3D 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. This problem has many applications in robotics such as intelligent vehicles, autonomous mapping and navigation. Many authors have introduced different approaches and algorithms. In this survey, we examine methods that have been proposed to segment 3D point clouds. The advantages, disadvantages, and design mechanisms of these methods are analyzed and discussed. Finally, we outline the promising future research directions.read more
Citations
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Autonomous vehicle perception: The technology of today and tomorrow
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Perception, Planning, Control, and Coordination for Autonomous Vehicles
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Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation
TL;DR: In this article, the authors summarized available data sets and relevant studies on recent developments in point cloud semantic segmentation and point cloud segmentation (PCS) for 3D point clouds.
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TL;DR: This work treats image segmentation as a graph partitioning problem and proposes a novel global criterion, the normalized cut, for segmenting the graph, which measures both the total dissimilarity between the different groups as well as the total similarity within the groups.
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Proceedings ArticleDOI
Normalized cuts and image segmentation
Jianbo Shi,Jitendra Malik +1 more
TL;DR: This work treats image segmentation as a graph partitioning problem and proposes a novel global criterion, the normalized cut, for segmenting the graph, which measures both the total dissimilarity between the different groups as well as the total similarity within the groups.
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