PRICAI 2004: PRICAI 2004: Trends in Artificial Intelligence pp 805-811 | Cite as
Adaptive Model for Foreground Extraction in Adverse Lighting Conditions
Conference paper
Abstract
Background elimination models are widely used in motion tracking systems. Our aim is to develop a system that performs reliably under adverse lighting conditions. In particular, this includes indoor scenes lit partly or entirely by diffuse natural light. We present a modified ”median value” model in which the detection threshold adapts to global changes in illumination. The responses of several models are compared, demonstrating the effectiveness of the new model.
Keywords
Gaussian Mixture Model Background Model Illumination Change Foreground Object Foreground Pixel
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References
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© Springer-Verlag Berlin Heidelberg 2004