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Output details

15 - General Engineering

University of Sussex

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Output 6 of 50 in the submission
Article title

Adaptive Sample Count Particle Filter

Type
D - Journal article
Title of journal
Computer Vision and Image Understanding
Article number
-
Volume number
116
Issue number
12
First page of article
1208
ISSN of journal
1077-3142
Year of publication
2012
Number of additional authors
4
Additional information

A method of adaptively controlling the sample count of a particle filter was developed. Additionally, an active area of support around the tracked object is employed which allows a more accurate colour histogram calculation. These methods are novel and reported here for the first time. Extensive experimental assessment is reported using thousands of frames of video from different scenarios. Tracking accuracy comparable to existing methods is achieved but the filter can be calculated up to five times faster. This contributed significantly to the author’s DSTL funded tracking research; rated highly upon completion: Contact Dr Peter Harvey, Tel: 01980616407, E-mail: prharvey@mail.dstl.gov.uk.

Interdisciplinary
-
Cross-referral requested
-
Research group
I - Industrial Informatics Signal Processing
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-