本文關(guān)鍵詞：基于深度信息的人體動作識別，由筆耕文化傳播整理發(fā)布。

摘要：

隨著低成本深度傳感器的發(fā)明，尤其是微軟 Kinect的出現(xiàn)，高分辨率的深度與視覺（RGB）感知數(shù)據(jù)被廣泛使用，并為解決計算機視覺領(lǐng)域中的基本問題開拓了新的機遇。本文針對基于深度信息的人體動作識別研究，首先提出了一種基于特征和數(shù)據(jù)類型的分類框架，，并對最近幾年提出的相關(guān)方法進行了全面回顧。隨后，對文獻中描述的算法進行了性能對比分析，同時對所引用的公共測試數(shù)據(jù)集進行了總結(jié)。最后，筆者對未來的研究方向進行了討論并給出了相關(guān)建議。

Abstract： 

With the invention of the low-cost depth sensors,especially the emergence of Microsoft Kinect,high-resolution depth and visual (RGB)sensing data has become available for widespread use,which opens up new opportunities to solve fundamental problems in computer vision commu-nity.This paper presents a comprehensive review of recent depth-based human action recognition algorithms.Firstly,we develop a taxonomic framework according to features and original data type.Following our taxonomy,recent published research on the use of depth data for recognizing human action is reviewed.Then,the publicly available datasets cited in their work are listed.Fi-nally,the authors discuss and suggest future research directions.

  本文關(guān)鍵詞：基于深度信息的人體動作識別，由筆耕文化傳播整理發(fā)布。