Improving 3D Point Cloud Segmentation Using Multimodal Fusion of Projected 2D Imagery Data : Improving 3D Point Cloud Segmentation Using Multimodal Fusion of Projected 2D Imagery Data

Improving 3D Point Cloud Segmentation Using Multimodal Fusion of Projected 2D Imagery Data : Improving 3D Point Cloud Segmentation Using Multimodal Fusion of Projected 2D Imagery Data

Semantic segmentation is a key approach to comprehensive image data analysis. It can be applied to analyze 2D images, videos, and even point clouds that contain 3D data points. On the first two problems, CNNs have achieved remarkable progress, but on point cloud segmentation, the results are less sa...

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Bibliographic Details
Main Author: He, Linbo
Format: Others
Language:English
Published: Linköpings universitet, Datorseende 2019
Subjects:
deep learning
multimodal fusion
multimodality
semantic segmentation
point cloud segmentation
Computer Vision and Robotics (Autonomous Systems)
Datorseende och robotik (autonoma system)
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157705

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157705

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