Deep learning assisted robust visual tracking with adaptive particle filtering

作者：

Highlights：

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• A simplified deep learning frame is applied into visual tracking.

• Simple network frame and adaptive particle filter make the tracker more robust especially when the quick movement occurs.

• This method is validated through subjective and objective metrics.

• Quantitative comparisons highlight the contributions of FC features and hand-crafted features.

摘要

•A simplified deep learning frame is applied into visual tracking.•Simple network frame and adaptive particle filter make the tracker more robust especially when the quick movement occurs.•This method is validated through subjective and objective metrics.•Quantitative comparisons highlight the contributions of FC features and hand-crafted features.

论文关键词：Visual tracking,Deep learning,Particle filter

论文评审过程：Received 2 March 2017, Revised 5 September 2017, Accepted 5 September 2017, Available online 21 September 2017, Version of Record 31 October 2017.

论文官网地址：https://doi.org/10.1016/j.image.2017.09.001