NDLI: Real-Time Keypoint Recognition Using Restricted Boltzmann Machine

Content Provider	IEEE Xplore Digital Library
Author	Miaolong Yuan Huajin Tang Haizhou Li
Copyright Year	2012
Abstract	Feature point recognition is a key component in many vision-based applications, such as vision-based robot navigation, object recognition and classification, image-based modeling, and augmented reality. Real-time performance and high recognition rates are of crucial importance to these applications. In this brief, we propose a novel method for real-time keypoint recognition using restricted Boltzmann machine (RBM). RBMs are generative models that can learn probability distributions of many different types of data including labeled and unlabeled data sets. Due to the inherent noise of the training data sets, we use an RBM to model statistical distributions of the training data. Furthermore, the learned RBM can be used as a competitive classifier to recognize the keypoints in real-time during the tracking stage, thus making it advantageous to be employed in applications that require real-time performance. Experiments have been conducted under a variety of conditions to demonstrate the effectiveness and generalization of the proposed approach.
Starting Page	2119
Ending Page	2126
Page Count	8
File Size	2443109
File Format	PDF
ISSN	2162237X
Volume Number	25
Issue Number	11
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Training data Real-time systems Data models Feature extraction Vectors Learning systems restricted Boltzmann machine (RBM). Classification deep learning feature matching keypoint recognition real-time tracking restricted Boltzmann machine (RBM)
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Computer Science Applications Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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