DocumentCode :
1776472
Title :
An integrated system for tracking and recognition using Kalman filter
Author :
Vijay, Akhil A. ; Johnson, Anoop K.
Author_Institution :
Dept. of Electron. & Commun. Eng., Mar Baselios Coll. of Eng. & Technol., Trivandrum, India
fYear :
2014
fDate :
10-11 July 2014
Firstpage :
1065
Lastpage :
1069
Abstract :
Tracking of any object from a video scene becomes more critical not only for security applications but also for analyzing traffic. This system integrates low level image processing as well as high level image processing through online data model and offline data model for more efficiency and robustness. Also this makes the system to handle occlusion conditions and abrupt color intensity variation conditions. This system uses median filtering and blob extraction for moving object detection. The offline model employs high level image processing recognize the moving objects. Here the Kalman filter is used for effective tracking under complex situations.
Keywords :
Kalman filters; data models; image colour analysis; median filters; object detection; object recognition; object tracking; video signal processing; Kalman filter; blob extraction; color intensity variation condition; high level image processing; integrated system; low level image processing; median filtering; moving object detection; object recognition; object tracking; occlusion condition; offline data model; online data model; robustness; security application; video scene; Data models; Equations; Image processing; Kalman filters; Mathematical model; Target tracking; Kalman filter; background substraction; morphological operations; object tracking; recognition; video tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014 International Conference on
Conference_Location :
Kanyakumari
Print_ISBN :
978-1-4799-4191-9
Type :
conf
DOI :
10.1109/ICCICCT.2014.6993118
Filename :
6993118
Link To Document :
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