%0 Journal Article
%T View-invariant action recognition:a survey<br>视点无关的行为识别综述
%A Feng Jiageng
%A Xiao jun
%A <br>冯家更
%A 肖俊
%J 中国图象图形学报
%D 2013
%I 
%X Vision-based human action recognition is currently one of the most active research fields. It has many promising applications such as intelligent surveillance, perceptual interface and content-based video retrieval. Even though, some hurdles still slower the development of action recognition, which the actions are often observed from arbitrary camera viewpoints in realistic scene. So view-invariance is important for action recognition, growing number of research groups to pay more attentions to research related to the view-invariant issue. This paper provides a survey on view-invariant recognition of poses and actions. The improvements of this topic in the last several years are discussed in detail from four aspects: space-time based methods, state-space approaches, dimension reduction based methods, and trajectories based methods. Public available standard datasets are presented, and the concluding discussion assesses the progress so far, and outlines some future directions.
%K view-invariant
%K action recognition
%K state-space
%K trajectories<br>视点无关
%K 行为识别
%K 状态空间
%K 降维
%K 轨迹
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=AE8DAD4245F3E9A95BB3E58DEDA045BB&yid=FF7AA908D58E97FA&vid=13553B2D12F347E8&iid=0B39A22176CE99FB&sid=0B4F496D54044D86&eid=BBF7D98F9BEDEC74&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=65