On the use of joint estimation in particle filters for object tracking in video

Prem Kuchi; Sethuraman Panchanathan

On the use of joint estimation in particle filters for object tracking in video

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Object tracking is an important problem, whose effective solution is crucial to lot of applications. Though several methods have been proposed in the literature, they fail when the object of interest does not conform to a specific process model. Also, current methods have to be tuned for different videos and objects (say, for example, using training data). One solution for such a problem is to estimate the parameters of the process model while estimating the state. In this paper, we propose such joint estimation of particle filters for object tracking and show that for the same model for state estimation, particle filtering with joint estimation performs better (in terms of the tracking error) than conventional particle filtering.

Original language	English (US)
Title of host publication	IEEE TENCON 2004 - 2004 IEEE Region 10 Conference Proceedings: Analog and Digital Techniques in Electrical Engineering
Volume	A
State	Published - 2004
Event	IEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering - Chiang Mai, Thailand Duration: Nov 21 2004 → Nov 24 2004

Other

Other	IEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering
Country/Territory	Thailand
City	Chiang Mai
Period	11/21/04 → 11/24/04

ASJC Scopus subject areas

General Engineering

Cite this

Kuchi, P & Panchanathan, S 2004, On the use of joint estimation in particle filters for object tracking in video. in IEEE TENCON 2004 - 2004 IEEE Region 10 Conference Proceedings: Analog and Digital Techniques in Electrical Engineering. vol. A, IEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering, Chiang Mai, Thailand, 11/21/04.

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author = "Prem Kuchi and Sethuraman Panchanathan",

year = "2004",

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volume = "A",

booktitle = "IEEE TENCON 2004 - 2004 IEEE Region 10 Conference Proceedings: Analog and Digital Techniques in Electrical Engineering",

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AU - Kuchi, Prem

AU - Panchanathan, Sethuraman

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AB - Object tracking is an important problem, whose effective solution is crucial to lot of applications. Though several methods have been proposed in the literature, they fail when the object of interest does not conform to a specific process model. Also, current methods have to be tuned for different videos and objects (say, for example, using training data). One solution for such a problem is to estimate the parameters of the process model while estimating the state. In this paper, we propose such joint estimation of particle filters for object tracking and show that for the same model for state estimation, particle filtering with joint estimation performs better (in terms of the tracking error) than conventional particle filtering.

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M3 - Conference contribution

AN - SCOPUS:27944462712

VL - A

BT - IEEE TENCON 2004 - 2004 IEEE Region 10 Conference Proceedings: Analog and Digital Techniques in Electrical Engineering

T2 - IEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering

Y2 - 21 November 2004 through 24 November 2004

ER -

On the use of joint estimation in particle filters for object tracking in video

Abstract

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ASJC Scopus subject areas

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