NDLI: Tracking Object by Combining Particle Filters and SIFT Features

Content Provider	IEEE Xplore Digital Library
Author	Bin Feng Bing Zeng Jinbo Qiu
Copyright Year	2009
Abstract	An object tracking algorithm based on the particle filter framework is proposed in this paper for video surveillance applications. The color histogram is combined with a scale invariant feature transform (SIFT) descriptor to represent the likelihood between the candidates and observed objects. They are then incorporated into the particle filter based tracking algorithm in order to achieve more robust and accurate results. As a complement to the similarity in color distribution, a measure of texture similarity is computed in terms of the number of matched SIFT key-points and the distance between two matched points. The use of a SIFT descriptor can enhance the tolerance to scale change, appearance variation, partial occlusion and cluttered background which are very popular in video surveillance practice. Experiments are provided to demonstrate that the performance of the proposed algorithm outperforms that of the traditional particle filter that makes use of the color histogram only.
Starting Page	527
Ending Page	532
File Size	1170555
Page Count	6
File Format	PDF
ISBN	9781424452378
DOI	10.1109/ICIG.2009.61
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optical filters Target tracking SIFT Particle tracking Distributed computing tracking Histograms Lighting particle filters Video surveillance Particle filters Robustness color histotogram Colored noise
Content Type	Text
Resource Type	Article

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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
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