Results 31 to 40 of about 105,450 (329)
IEEE Access, 2023 As a critical step in 3D scene understanding, semantic segmentation of point clouds has broad application scenarios, including intelligent driving, augmented reality, smart factories, etc.
Ansi Zhang +4 more
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3D environment mapping using the Kinect V2 and path planning based on RRT algorithms [PDF]
, 2016 This paper describes a 3D path planning system that is able to provide a solution trajectory for the automatic control of a robot. The proposed system uses a point cloud obtained from the robot workspace, with a Kinect V2 sensor to identify the interest ...
Aguilar Castillo, Wilbert Geovanny +1 more
core +3 more sources
Point Cloud Semantic Segmentation
, 2023 7 pages, 2 figures, 8 tables Language ...
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Point attention network for semantic segmentation of 3D point clouds [PDF]
Pattern Recognition, 2020 Submitted to a ...
Mingtao Feng +4 more
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A new framework for interactive segmentation of point clouds [PDF]
, 2014 Point cloud segmentation is a fundamental problem in point processing. Segmenting a point cloud fully automatically is very challenging due to the property of point cloud as well as different requirements of distinct users.
Boehm, J, Liu, K
core +3 more sources
Point clouds segmentation of rapeseed siliques based on sparse-dense point clouds mapping
Frontiers in Plant Science, 2023 In this study, we propose a high-throughput and low-cost automatic detection method based on deep learning to replace the inefficient manual counting of rapeseed siliques. First, a video is captured with a smartphone around the rapeseed plants in the silique stage.
Yuhui Qiao +14 more
openaire +3 more sources
Learning to Optimally Segment Point Clouds [PDF]
IEEE Robotics and Automation Letters, 2020 We focus on the problem of class-agnostic instance segmentation of LiDAR point clouds. We propose an approach that combines graph-theoretic search with data-driven learning: it searches over a set of candidate segmentations and returns one where individual segments score well according to a data-driven point-based model of "objectness".
Peiyun Hu, David Held, Deva Ramanan
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A Deep Neural Network Using Double Self-Attention Mechanism for ALS Point Cloud Segmentation
IEEE Access, 2022 Airborne laser scanning (ALS) point cloud segmentation is an essential procedure for 3D data understanding and applications. This task is challenging due to the unstructured, disordered, and sparse distribution of the point cloud. PointNet++
Lili Yu, Haiyang Yu, Shuai Yang
doaj +1 more source
A self-adaptive segmentation method for a point cloud [PDF]
, 2018 The segmentation of a point cloud is one of the key technologies for three-dimensional reconstruction, and the segmentation from three-dimensional views can facilitate reverse engineering. In this paper, we propose a self-adaptive segmentation algorithm,
A Rodriguez +27 more
core +1 more source
Rethinking 3-D LiDAR Point Cloud Segmentation [PDF]
IEEE Transactions on Neural Networks and Learning SystemsTNNLS ...
Shijie Li, Yun Liu, Juergen Gall
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