Going deeper into action recognition: A survey
作者：
Highlights：
• We provide a detailed review of the work on human action recognition over the past decade.
• We refer to “actions” as meaningful human motions.
• Including Hand-crafted representations methods, we review the impact of Deep-nets on action recognition.
• We follow a systematic taxonomy to highlight the essence of both Hand-crafted and Deep-net solutions.
• We present a comparison of methods at their algorithmic level and performance.
摘要
•We provide a detailed review of the work on human action recognition over the past decade.•We refer to “actions” as meaningful human motions.•Including Hand-crafted representations methods, we review the impact of Deep-nets on action recognition.•We follow a systematic taxonomy to highlight the essence of both Hand-crafted and Deep-net solutions.•We present a comparison of methods at their algorithmic level and performance.
论文关键词：Human action recognition,Motion recognition,Survey,Deep networks
论文评审过程：Received 16 May 2016, Revised 14 October 2016, Accepted 25 January 2017, Available online 16 February 2017, Version of Record 22 March 2017.
论文官网地址：https://doi.org/10.1016/j.imavis.2017.01.010
