Dynamic scene understanding using temporal association rules

作者：

Highlights：

• Uses temporal mining technique event recognition in dynamic scenes

• Temporal association rules are then generated from frequent patterns. These association rules help model the sequence cycle.

• Spatio-temporal anomalies are identified and detected in a hierarchical manner.

摘要

•Uses temporal mining technique event recognition in dynamic scenes•Temporal association rules are then generated from frequent patterns. These association rules help model the sequence cycle.•Spatio-temporal anomalies are identified and detected in a hierarchical manner.

论文关键词：Scene understanding,Computer vision,Association rules,Traffic surveillance

论文评审过程：Received 23 July 2013, Revised 12 April 2014, Accepted 28 August 2014, Available online 20 October 2014.

论文官网地址：https://doi.org/10.1016/j.imavis.2014.08.010