NDLI: Point match refinement through rigidity constraint and vote

Content Provider	IET Digital Library
Author	Liu, Yonghuai Zhao, Yitian Li, Longzhuang Han, Jiwan
Abstract	Feature extraction and matching has been widely used for the registration of overlapping partial shapes. However, the established tentative point matches (TPMs) usually include a large proportion of false ones due to a number of factors: imaging noise, occlusion, repetitive structures, and cluttered background. To apply the rigidity constraint to refine these TPMs in three main steps is proposed. First, a set of one-to-many point matches is established, then use them to vote against each other, and finally select such TPMs with the same surface type, the minimum error, and the most votes significantly more than the second most ones as the more reliable ones. A comparative study using real data captured by a Microsoft Kinect sensor shows that the refinement is successful.
Starting Page	1304
Ending Page	1306
Page Count	3
ISSN	00135194
Volume Number	52
e-ISSN	1350911X
Issue Number	Issue 15, Jul (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/52/15
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2016.1643
Journal	Electronics Letters
Publisher Date	2016-06-29
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Cluttered Background Computer Vision And Image Processing Technique Feature Extraction Feature Matching Image Denoising Image Matching Image Recognition Image Registration Image Sonsor Imaging Noise Microsoft Kinect Sensor Overlapping Partial Shapes Point Match Refinement Repetitive Structure
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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