NDLI: Multi-part histogram based visual tracking with maximum of posteriori

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2010 2nd International Conference on Computer Engineering and Technology

Volume 7 - 2010

Volume 6 - 2010

Parallel AES algorithm for fast Data Encryption on GPU

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Real time acoustic echo cancellation technique based on normalized least mean square method

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Volume 5 - 2010

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Volume 3 - 2010

Volume 2 - 2010

Volume 1 - 2010

2009 International Conference on Computer Engineering and Technology

Multi-part histogram based visual tracking with maximum of posteriori

Content Provider	IEEE Xplore Digital Library
Author	Islam, M.Z. Chi-Min Oh Jun Sung Lee Chil-Woo Lee
Copyright Year	2010
Description	Author affiliation: Dept. of Computer Engineering, Chonnam National University, Gwangju 500-757, KOREA (Islam, M.Z.; Chi-Min Oh; Jun Sung Lee; Chil-Woo Lee)
Abstract	This paper presents a new multi-part histogram (MPH) based algorithm for non-rigid object tracking with Particle filtering state estimation approach. The reference and target object are represented by some sub-region with integral image technique. Each region has its own histogram and we calculate the weight of each particle based on its region position of target object. The most weighted particle settles on the centre position of the bounded target and gradually decreases the weight of particle vertically and horizontally from the centre position. For smooth tracking Maximum a Posteriori (MAP) is introduced for better observation likelihood calculations. Experiments of proposed tracker show that our system is robust against false target tracking, severe occlusion, and rotation, scaling without extra computational cost.
File Size	1380428
File Format	PDF
ISBN	9781424463473
e-ISBN	9781424463497
DOI	10.1109/ICCET.2010.5486150
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Target tracking Bayesian estimation Multi-part histogram Particle tracking Histograms Bayesian methods particle filtering Filtering algorithms Sampling methods Particle filters Noise robustness Computational efficiency State estimation maximum a posteriori
Content Type	Text
Resource Type	Article

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