NDLI: Vision-based wheelchair navigation using geometric AdaBoost learning

Content Provider	IET Digital Library
Author	Kim, Eun Yi
Abstract	A novel training algorithm called geometric AdaBoost learning, which integrates the local-appearance models with the explicit shape model is proposed. The proposed algorithm employs a two-stage AdaBoost learning algorithm. The first-stage learning is performed to learn the local texture model within local image patches and to produce a confidence map. Based on the confidence values, the high-discriminative local patches are selected, and then the global context models between them are trained in the later stage using AdaBoost learning. The proposed algorithm is applied to wheelchair navigation, and the results demonstrate that it outperforms the state-of-the-art algorithms with improvements of 23.3 and 49% in terms of accuracy and speed.
Starting Page	534
Ending Page	536
Page Count	3
ISSN	00135194
Volume Number	53
e-ISSN	1350911X
Issue Number	Issue 8, Apr (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/53/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2016.3865
Journal	Electronics Letters
Publisher Date	2017-03-21
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Combinatorial Mathematics Communication Computing Computer Vision And Image Processing Technique Geometric AdaBoost Learning Training Algorithm Geometry Global Context Model High-discriminative Local Image Patch Selection Image Texture Knowledge Engineering Technique Learning in AI Local Texture Model Navigation Optical, Image And Video Signal Processing Radio Navigation And Direction Finding Telecommunication Computing Two-stage AdaBoost Learning Algorithm Vision-based Wheelchair Navigation Wheelchairs
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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

Learned geometric features of 3D range data for human and tree recognition

Traffic sign recognition based on weighted ELM and AdaBoost

Gentle Adaboost algorithm based on multi-feature fusion for face detection

Image patch prior learning based on random neighbourhood resampling for image denoising

Multi-sensor-based online positive learning for drivable region detection

Recognising human interaction from videos by a discriminative model

Detection of partially occluded pedestrians by an enhanced cascade detector

Variational Bayesian learning for background subtraction based on local fusion feature

Identification of wool and mohair fibres with texture feature extraction and deep learning

Vision-based wheelchair navigation using geometric AdaBoost learning

Similar Documents

Learned geometric features of 3D range data for human and tree recognition

Traffic sign recognition based on weighted ELM and AdaBoost

Gentle Adaboost algorithm based on multi-feature fusion for face detection

Image patch prior learning based on random neighbourhood resampling for image denoising

Multi-sensor-based online positive learning for drivable region detection

Recognising human interaction from videos by a discriminative model

Detection of partially occluded pedestrians by an enhanced cascade detector

Variational Bayesian learning for background subtraction based on local fusion feature

Identification of wool and mohair fibres with texture feature extraction and deep learning

Vision-based wheelchair navigation using geometric AdaBoost learning