Surveillance Applications of Biologically-Inspired Smart Cameras

Kosta Haltis; Lee Andersson; Matthew Sorell; Russell Brinkworth

Forensics in Telecommunications, Information and Multimedia. Second International Conference, e-Forensics 2009, Adelaide, Australia, January 19-21, 2009, Revised Selected Papers

Research Article

Surveillance Applications of Biologically-Inspired Smart Cameras

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@INPROCEEDINGS{10.1007/978-3-642-02312-5_8,
    author={Kosta Haltis and Lee Andersson and Matthew Sorell and Russell Brinkworth},
    title={Surveillance Applications of Biologically-Inspired Smart Cameras},
    proceedings={Forensics in Telecommunications, Information and Multimedia. Second International Conference, e-Forensics 2009, Adelaide, Australia, January 19-21, 2009, Revised Selected Papers},
    proceedings_a={E-FORENSICS},
    year={2012},
    month={5},
    keywords={Surveillance digital video processing biological vision motion detection image enhancement},
    doi={10.1007/978-3-642-02312-5_8}
}

Kosta Haltis
Lee Andersson
Matthew Sorell
Russell Brinkworth
Year: 2012
Surveillance Applications of Biologically-Inspired Smart Cameras
E-FORENSICS
Springer
DOI: 10.1007/978-3-642-02312-5_8

Kosta Haltis¹, Lee Andersson¹, Matthew Sorell¹, Russell Brinkworth²^,*

1: School of Electrical and Electronic Engineering
2: University of Adelaide

*Contact email: russell.brinkworth@adelaide.edu.au

Abstract

Biological vision systems are capable of discerning detail and detecting motion in a wide range of highly variable lighting conditions. We describe the real-time implementation of a biological vision model using a high dynamic range video camera and a General Purpose Graphics Processing Unit (GPGPU) and demonstrate the effectiveness of the implementation in two surveillance applications: dynamic equalization of contrast for improved recognition of scene detail; and the use of biologically-inspired motion processing for the detection of small or distant moving objects in a complex scene.

Keywords: Surveillance digital video processing biological vision motion detection image enhancement

Published: 2012-05-11

: http://dx.doi.org/10.1007/978-3-642-02312-5_8