NDLI: Robust multi-directional bicycle recognition on the rotation using the stereo vision

Content Provider	IEEE Xplore Digital Library
Author	Fukushima, K. Matsushima, K.
Copyright Year	2015
Description	Author affiliation: Mechanical and Electrical Systems Engineering Advanced Course Advanced Engineering School National Institute of Technology, Kurume College Komorino 1-1-1, Kurume-shi Fukuoka, 830-8555 Japan (Fukushima, K.) \|\| Department of Control and Information Systems Engineering National Institute of Technology, Kurume College Komorino 1-1-1, Kurume-shi Fukuoka, 830-8555 Japan (Matsushima, K.)
Abstract	Many researches have worked for the development of automotive technologies, so as to realize a convenient and safety automotive society such as Advanced Safety Vehicle (ASV) and Traffic Monitoring System (TMS). As a result, traffic accidents have decreased as the years pass, and the number of the dead and injuries have been reduced. However, autonomous driving is not only required to detect bicycles around vehicles, but also expected to understand the behaviors of bicycles. In addition, since the proportion of bicycle accident shows a high percentage in the total traffic accident, it has been predicted an increase of the accident of the bicycle in the future. Therefore we propose a multi-directional bicycle recognition system using the distance information obtained by the stereo camera. In the proposed system, we divide the moving direction of the bicycle into three directions. In addition, we propose a robust feature extraction method on rotation in order to cope with the bicycle between each direction. Finally,we show the experimental results and verify the effectiveness of the proposed method.
Starting Page	36
Ending Page	40
File Size	448634
Page Count	5
File Format	PDF
e-ISBN	9781467391146
DOI	10.1109/ICVES.2015.7396890
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-05
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Shape Bicycles Feature extraction Cameras Safety Mathematical model
Content Type	Text
Resource Type	Article

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

Robust multi-directional bicycle recognition on the rotation using the in-vehicle cameras

Bicycle tracking using ellipse extraction

Road environment recognition method in complex traffic situations based on stereo vision

Applying MSC-HOG feature to the detection of a human on a bicycle

Wheelchair recognition by using stereo vision and histogram of oriented gradients (HOG) in real environments

Robust place recognition with stereo cameras

Pedestrian recognition using stereo vision and Histogram of Oriented Gradients

Stereo matching between images of large slope based on multi-scale directional wavelet transform

Applying HOG feature to the detection and tracking of a human on a bicycle

Robust multi-directional bicycle recognition on the rotation using the stereo vision

Similar Documents

Robust multi-directional bicycle recognition on the rotation using the in-vehicle cameras

Bicycle tracking using ellipse extraction

Road environment recognition method in complex traffic situations based on stereo vision

Applying MSC-HOG feature to the detection of a human on a bicycle

Wheelchair recognition by using stereo vision and histogram of oriented gradients (HOG) in real environments

Robust place recognition with stereo cameras

Pedestrian recognition using stereo vision and Histogram of Oriented Gradients

Stereo matching between images of large slope based on multi-scale directional wavelet transform

Applying HOG feature to the detection and tracking of a human on a bicycle

Robust multi-directional bicycle recognition on the rotation using the stereo vision