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3D Super-resolution Approach for Sparse Laser Scanner Data : Volume Ii-3/W5, Issue 1 (19/08/2015)

By Hosseinyalamdary, S.

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Book Id: WPLBN0004013888
Format Type: PDF Article :
File Size: Pages 7
Reproduction Date: 2015

Title: 3D Super-resolution Approach for Sparse Laser Scanner Data : Volume Ii-3/W5, Issue 1 (19/08/2015)  
Author: Hosseinyalamdary, S.
Volume: Vol. II-3/W5, Issue 1
Language: English
Subject: Science, Isprs, Annals
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Hosseinyalamdary, S., & Yilmaz, A. (2015). 3D Super-resolution Approach for Sparse Laser Scanner Data : Volume Ii-3/W5, Issue 1 (19/08/2015). Retrieved from

Description: Photogrammetric Computer Vision (PCV) Lab 2070 Neil Avenue, Columbus, OH 43212, USA. Laser scanner point cloud has been emerging in Photogrammetry and computer vision to achieve high level tasks such as object tracking, object recognition and scene understanding. However, low cost laser scanners are noisy, sparse and prone to systematic errors. This paper proposes a novel 3D super resolution approach to reconstruct surface of the objects in the scene. This method works on sparse, unorganized point clouds and has superior performance over other surface recovery approaches. Since the proposed approach uses anisotropic diffusion equation, it does not deteriorate the object boundaries and it preserves topology of the object.



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