Dynamic Codebook for Foreground Segmentation in a Video

The foreground segmentation in a video is a way to extract changes in image sequences. It is a key task in an early stage of many applications in the computer vision area. The information of changes in the scene must be segmented before any further analysis could be taken place. However, it remains with difficulties caused by several real-world challenges such as cluttered backgrounds, changes of the illumination, shadows, and long-term scene changes. This paper proposes a novel method, namely a dynamic codebook (DCB), to address such challenges of the dynamic backgrounds. It relies on a dynamic modeling of the background scene. Initially, a codebook is constructed to represent the background information of each pixel over a period of time. Then, a dynamic boundary of the codebook will be made to support variations of the background. The revised codebook will always be adaptive to the new background's environments. This makes the foreground segmentation more robust to the changes of background scene. The proposed method has been evaluated by using the changedetection.net (CDnet) benchmark which is a well-known video dataset for testing change-detection algorithms. The experimental results and comprehensive comparisons have shown a very promising performance of the proposed method.