A Self-adaptive CodeBook (SACB) model for real-time background subtraction
作者：
Highlights：
• This paper presents a Self-adaptive CodeBook background model for moving object segmentation in a video.
• Several new techniques are introduced to enhance the performance of standard CodeBook model.
• The proposed model gives better processing speed than the standard CodeBook model.
• New color model and the automatic parameter estimation mechanism help to achieve better accuracy than the standard CodeBook model.
• The proposed model gives a real-time performance and a good balance between segmentation accuracy and processing efficiency.
摘要
•This paper presents a Self-adaptive CodeBook background model for moving object segmentation in a video.•Several new techniques are introduced to enhance the performance of standard CodeBook model.•The proposed model gives better processing speed than the standard CodeBook model.•New color model and the automatic parameter estimation mechanism help to achieve better accuracy than the standard CodeBook model.•The proposed model gives a real-time performance and a good balance between segmentation accuracy and processing efficiency.
论文关键词：Background subtraction,Video processing,Parameter learning,Background modeling,CodeBook model
论文评审过程：Received 4 October 2013, Revised 7 November 2014, Accepted 7 February 2015, Available online 15 April 2015, Version of Record 15 May 2015.
论文官网地址：https://doi.org/10.1016/j.imavis.2015.02.001
