DocumentCode :
2619806
Title :
Adaptive thresholding using particle filter for tracking small and low contrast objects
Author :
Malik, Mohammad Bilal ; Ali, Usman
Author_Institution :
Dept. of Electr. Eng., Nat. Univ. of Sci. & Technol., Islamabad, Pakistan
fYear :
2010
fDate :
10-13 May 2010
Firstpage :
205
Lastpage :
208
Abstract :
In this paper, we present a simple and robust method for tracking small and low contrast objects in video sequences. The technique is based on image segmentation by adaptive thresholding, which is done using a particle filter. In order to achieve this, the threshold is made a state of the system dynamics. Prior knowledge of the target attributes such as position, size and mean intensity are incorporated into the tracking algorithm. This novel idea resolves many challenging issues faced by most of the tracking algorithms e.g. sudden illumination changes, unpredictable motion and incorrect model update in consecutive frames.
Keywords :
image segmentation; image sequences; particle filtering (numerical methods); tracking; video signal processing; adaptive thresholding; image segmentation; low contrast objects; particle filter; system dynamics; tracking algorithm; video sequences; Atmospheric modeling; Computational modeling; Fractals; Robustness; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-7165-2
Type :
conf
DOI :
10.1109/ISSPA.2010.5605539
Filename :
5605539
Link To Document :
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