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Content-based 3D image retrieval using point cloud library a novel approach for the retrieval of 3D images

Publication Type : Conference Paper

Publisher : Proceedings of the 2017 IEEE International Conference on Communication and Signal Processing, ICCSP 2017

Source : Proceedings of the 2017 IEEE International Conference on Communication and Signal Processing, ICCSP 2017, Institute of Electrical and Electronics Engineers Inc. (2017)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046694200&doi=10.1109%2fICCSP.2017.8286478&partnerID=40&md5=d9bafd8a3b2292c32adad257d2fa4ff1

ISBN : 9781509038008

Keywords : Clustering, Content based image retrieval, Content based retrieval, Feature extraction, Image processing, Keypoints, Normalization, Point cloud, Retrieval process, Software and hardwares, Technological advancement, Three dimensional computer graphics

Campus : Amritapuri

School : Department of Computer Science and Engineering, School of Engineering

Center : Electronics Communication and Instrumentation Forum (ECIF)

Department : Computer Science, Electrical and Electronics, Sciences

Verified : Yes

Year : 2017

Abstract : Retrieval by content of 3D images has become an area of utmost interest at present. Unlike earlier times, 3D imaging is more affordable owing to the reduction in the software and hardware costs. Hence there has been an increasing degree of technological advancements in this field trying to meet the increasing demand. One such area of interest is content-based image retrieval i.e. obtaining similar 3D images on providing an input 3D image. In content-based image retrieval, the features like texture and shape of the input image are considered for the retrieval process. In this paper, a method for content-based 3D image retrieval using point cloud library is put forth. Point Cloud Library (PCL) is an open project for 2D/3D images and point cloud processing. Here different stages of retrieving the 3D image are by concentrating on 4 major steps i.e. key-point detection, feature extraction, comparison and visualization. The result would be the retrieval of a set of 3D images that are best matched with the input image. © 2017 IEEE.

Cite this Research Publication : G. Aiswarya, Valsaraj, N., Vaishak, M., Nair, T. U., Karthik, V., and Jyothisha J. Nair, “Content-based 3D image retrieval using point cloud library a novel approach for the retrieval of 3D images”, in Proceedings of the 2017 IEEE International Conference on Communication and Signal Processing, ICCSP 2017, 2017

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