Spatio-contextual Gaussian mixture model for local change detection in underwater video

作者：

Highlights：

• MoG integrated with Wronskian framework for underwater local change detection.

• Linear dependency of a pixel with background model is tested using Wronskian.

• Objects can be detected efficiently in blurred and dynamic environment.

• Adaptive weight updating for background model.

摘要

•MoG integrated with Wronskian framework for underwater local change detection.•Linear dependency of a pixel with background model is tested using Wronskian.•Objects can be detected efficiently in blurred and dynamic environment.•Adaptive weight updating for background model.

论文关键词：Underwater surveillance,Wronskian framework,Object detection,Background subtraction

论文评审过程：Received 2 August 2017, Revised 5 November 2017, Accepted 5 December 2017, Available online 7 December 2017, Version of Record 21 December 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.12.009