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On stable dynamic background generation technique using gaussian mixture models for robust object detection

conference contribution
posted on 2023-02-07, 23:58 authored by M Haque, Manzur MurshedManzur Murshed, M Paul
Gaussian mixture models (GMM) is used to represent the dynamic background in a surveillance video to detect the moving objects automatically. All the existing GMM based techniques inherently use the proportion by which a pixel is going to observe the background in any operating environment. In this paper we first show that such a proportion not only varies widely across different scenarios but also forbids using very fast learning rate. We then propose a dynamic background generation technique in conjunction with basic background subtraction which detected moving objects with improved stability and superior detection quality on a wide range of operating environments in two sets of benchmark surveillance sequences. © 2008 IEEE.

History

Pagination

41-48

Start date

2008-09-01

End date

2008-09-03

ISBN-13

9780769533414

Title of proceedings

Proceedings - IEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008

Event

2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance (AVSS)

Publisher

IEEE

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