NDLI: Vessel tracking vision system using a combination of Kaiman filter, Bayesian classification, and adaptive tracking algorithm

Content Provider	IEEE Xplore Digital Library
Author	Yun Jip Kim Yun Koo Chung Byung Gil Lee
Copyright Year	2014
Description	Author affiliation: ETRI (Electron. & Telecommun. Res. Inst.), Daejeon, South Korea (Yun Koo Chung; Byung Gil Lee) \|\| Dept. of Inf. Security Eng., UST (Univ. of Sci. & Technol.), Daejeon, South Korea (Yun Jip Kim)
Abstract	In these days, there are many vessel traffics to trade with foreign nations and travel abroad. Near coast or in harbor, the more traffics of transportation, the more possibility of accidents tends to occur. Thus, to reduce ships collision, vessel traffic services (VTS) centers have installed lots of equipment to keep a close eye on ships sailing in sea port, such as night observation device, telescope, and CCTV. To improve efficiently existing tracking system and overcome flaw of noises in the process of pursuit in maritime environment, considering bad weather and waves, this paper presents vessel tracking system using an image input device. The tracking system uses a fusion of Bayesian classifier to distinguish some images at initial stage, Kalman filter algorithm for keeping tracking the watercraft when it cannot be detected from the obtained image because some noises or inappropriate parameters used in the library functions may prevent detection from successive pictures, and the adaptive tracking algorithm for not only whether Kalman filtering is used as adaptive way to reduce a computational time but also disregarding the noise interference. The experimental results are included to prove the validity of the proposed method.
Sponsorship	IEEE Commun. Soc.
Starting Page	196
Ending Page	201
File Size	3256992
Page Count	6
File Format	PDF
e-ISBN	9788996865032
DOI	10.1109/ICACT.2014.6778948
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-02-16
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Global IT Research Institute (GIRI)
Subject Keyword	Kalman filters Bayes methods Streaming media Classification algorithms Noise Marine vehicles Feature extraction Object Detection Adaptive Tracking with Kaiman Filter Bayesian Classifier Vessel Tracking
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

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