An improved background subtraction approach in target detection and tracking
Hao Lai, Yuesheng Zhu, Zhenming Nong · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
In this paper, a novel background subtraction approach is proposed to avoid stationary foreground objects being merged into the background in target detection and tracking, in which an improved background model is designed by using virtual frames and the blur can be attenuated with this model when an object moves again after it stays for a long time. Moreover, the proposed model is fused with the eigenbackgrounds to improve the environmental adaptability. Our experimental results indicate that the proposed approach enhances the performance of target detection and tracking in intelligent surveillance and is superior to some state-of-the-art methods according to the precision-recall measurement.