摘要
Background subtraction, where the foreground is segmented from the background, is the first step of data analysis and processing in automated visual surveillance. Aiming to solve the problems associated with dynamic, multi-modal background, we explore a new approach which can handle the unconstrained environment. Based on multiclass support vector machines, a new MSVM is proposed for the classification of the background and the foreground. The simulation indicates our proposed algorithm is feasible.
- 出版日期2015
- 单位华南师范大学