Pedestrian recognition in multi-camera networks using multilevel important salient feature and multicategory incremental learning
作者：
Highlights：
• Multilevel important salient map and colour feature for robust appearance modeling.
• A novel multicategory incremental modeling for accurate realtime object recognition.
• Only few samples for building an accurate classification model.
• New target objects can be effectively recognized after incremental learning.
• Better performance in accuracy, robustness and computation efficiency.
摘要
•Multilevel important salient map and colour feature for robust appearance modeling.•A novel multicategory incremental modeling for accurate realtime object recognition.•Only few samples for building an accurate classification model.•New target objects can be effectively recognized after incremental learning.•Better performance in accuracy, robustness and computation efficiency.
论文关键词：Video pedestrian recognition,Collaborative multi-camera surveillance,MImSF,ORMIM,Incremental learning,Non-overlapping camera network
论文评审过程：Received 10 February 2016, Revised 31 December 2016, Accepted 29 January 2017, Available online 3 February 2017, Version of Record 2 March 2017.
论文官网地址：https://doi.org/10.1016/j.patcog.2017.01.033
