An Adaptive Codebook Model for Change Detection with Dynamic Background

Codebook model is a widely used method for segmenting foreground pixels. However, it is often generate erroneous positive result in case of dynamic background. This paper proposed an adaptive codebook model for change detection to disparate static background from dynamic background. To eliminate shadow/illumination effects cone-shaped color distance map is utilized in lieu of cylindrical. Moreover multi-layer codebook model is proposed containing codebooks for each pixel that is used to separate dynamic background from static background region. Proposed method reduces erroneous positive foreground pixels detected conventionally when pixel belongs to background shows dynamic behaviour. During experimentation proposed method is tested over numerous videos with complex illumination and background situations. The experimental result shows improvement over basic codebook model and other state-of-art background subtraction model.