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. © Springer-Verlag Berlin Heidelberg 2004.
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CITATION STYLE
Greenhill, S., Venkatesh, S., & West, G. (2004). Adaptive model for foreground extraction in adverse lighting conditions. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3157, pp. 805–811). Springer Verlag. https://doi.org/10.1007/978-3-540-28633-2_85
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