NDLI: Appearance and Geometry Fusion for Enhanced Dense 3D Alignment

Content Provider	IEEE Xplore Digital Library
Author	Nascimento, E.R. Schwartz, W.R. Oliveira, G.L. Veira, A.W. Campos, M.F.M. Mesquita, D.B.
Copyright Year	2012
Abstract	This work proposes a novel RGB-D feature descriptor called Binary Appearance and Shape Elements (BASE) that efficiently combines intensity and shape information to improve the discriminative power and enable an enhanced and faster matching process. The new descriptor is used to align a set of RGB point clouds to generate dense three dimensional models of indoor environments. We compare the performance of state-of-the-art feature descriptors with the proposed descriptor for scene alignment through the registration of multiple indoor textured depth maps. Experimental results show that the proposed descriptor outperforms the other approaches in computational cost, memory consumption and match quality. Additionally, experiments based on cloud alignment show that the BASE descriptor is suitable to be used in the registration of RBG-D data even when the environment is partially illuminated.
Starting Page	47
Ending Page	54
File Size	2883065
Page Count	8
File Format	PDF
ISBN	9781467328029
ISSN	15301834
e-ISBN	9780769548296
DOI	10.1109/SIBGRAPI.2012.16
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-22
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Shape Histograms Iterative closest point algorithm Vectors Robustness Memory management Three-dimensional Mapping Descriptor RGB-D Camera Reconstruction Registration
Content Type	Text
Resource Type	Article

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