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.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-642-02312-5_25
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© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Haltis, K., Andersson, L., Sorell, M., Brinkworth, R. (2009). Surveillance Applications of Biologically-Inspired Smart Cameras. In: Sorell, M. (eds) Forensics in Telecommunications, Information and Multimedia. e-Forensics 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 8. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02312-5_8
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DOI: https://doi.org/10.1007/978-3-642-02312-5_8
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