Background Subtraction Using Running Gaussian Average: a Color Channel Comparison
نویسنده
چکیده
Background subtraction methods are widely used to detect moving objects from static cameras. Many different methods have been proposed, reviewed and categorised based on their complexity, speed, memory requirements and accuracy. The Running Gaussian Average is a simple method offering acceptable accuracy and high frame rate while having low memory requirements. Originally this method was proposed for intensity images, but extensions to other color spaces such as (R,G,B), (Y,U,V) and others can be made. In this paper, we adapt this method to the (R,G,B) color space, compare the results with the singlecomponent intensity color space. Further we discuss the results of the comparison and provide an analysis of the relation between both color models.
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