Background subtraction methods in video streams: A review

• Published in: 2015 4th International Conference on Interactive Digital Media (ICIDM) pp. 1 - 6
• Main Authors: Joudaki, Saba, Shahrizal Bin Sunar, Mohd, Kolivand, Hoshang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-12-2015
• Subjects: Background Subtraction; Computer Vision; Estimation; Filtering; Hidden Markov models; Image Processing; Lighting; Memory management; Streaming media; Video surveillance
• DOI: 10.1109/IDM.2015.7516329

Background subtraction is one of the most important parts in image and video processing field. There are some unnecessary parts during the image or video processing, and should be removed, because they lead to more execution time or required memory. Several subtraction methods have been presented for the time being, but find the best-suited method is an issue, which this study is going to address. This paper presents a comparative study of several existing background subtraction methods which have been investigated from simple background subtraction to more complex statistical techniques. The goal of this study is to provide a view of the strengths and drawbacks of the widely used methods. The methods are compared based on their memory requirement, the computational time and their robustness of different videos. Finally, a comparison between the existing methods has been employed with some factors like computational time or memory requirements.