Influence of colour and feature geometry on multi-modal 3D point clouds data registration
Influence of colour and feature geometry on multi-modal 3D point clouds data registration
With the current transition of various digital contents from 2D to 3D, the problem of 3D data matching and registration is increasingly important. Registration of multimodal 3D data acquired from different sensors remains a challenging problem due to the difference in types and characteristics of the data. In this paper, we evaluate the registration performance of 3D feature descriptors with different domains on datasets from various environments and modalities. Datasets are acquired in indoor and outdoor environments with 2D and 3D sensing devices including LIDAR, spherical imaging, digital camera and RGBD camera. FPFH, PFH and SHOT feature descriptors are applied to the 3D point clouds generated from the multi-modal datasets. Local neighbouring point distribution, keypoints distribution, colour information and their combinations are used for feature description. Finally we analyse their influences on the multi-modal 3D point clouds data registration. © 2014 IEEE.
Colour informations, Current transitions, Data registration, Different domains, Feature description, Feature descriptors, Outdoor environment, Registration performance, Digital devices
202-209
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
2015
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
Kim, H. and Hilton, Adrian
(2015)
Influence of colour and feature geometry on multi-modal 3D point clouds data registration.
2nd International Conference on 3D Vision, , Tokyo, Japan.
08 - 11 Dec 2014.
.
(doi:10.1109/3DV.2014.51).
Record type:
Conference or Workshop Item
(Paper)
Abstract
With the current transition of various digital contents from 2D to 3D, the problem of 3D data matching and registration is increasingly important. Registration of multimodal 3D data acquired from different sensors remains a challenging problem due to the difference in types and characteristics of the data. In this paper, we evaluate the registration performance of 3D feature descriptors with different domains on datasets from various environments and modalities. Datasets are acquired in indoor and outdoor environments with 2D and 3D sensing devices including LIDAR, spherical imaging, digital camera and RGBD camera. FPFH, PFH and SHOT feature descriptors are applied to the 3D point clouds generated from the multi-modal datasets. Local neighbouring point distribution, keypoints distribution, colour information and their combinations are used for feature description. Finally we analyse their influences on the multi-modal 3D point clouds data registration. © 2014 IEEE.
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Published date: 2015
Venue - Dates:
2nd International Conference on 3D Vision, , Tokyo, Japan, 2014-12-08 - 2014-12-11
Keywords:
Colour informations, Current transitions, Data registration, Different domains, Feature description, Feature descriptors, Outdoor environment, Registration performance, Digital devices
Identifiers
Local EPrints ID: 440919
URI: http://eprints.soton.ac.uk/id/eprint/440919
PURE UUID: b125b1a6-66c1-4533-a421-e297c44e58ef
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Date deposited: 22 May 2020 16:38
Last modified: 17 Mar 2024 04:01
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Author:
H. Kim
Author:
Adrian Hilton
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