DocumentCode
692054
Title
Multi-view Human Action Recognition: A Survey
Author
Iosifidis, Alexandros ; Tefas, Anastasios ; Pitas, Ioannis
Author_Institution
Dept. of Inf., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece
fYear
2013
fDate
16-18 Oct. 2013
Firstpage
522
Lastpage
525
Abstract
While single-view human action recognition has attracted considerable research study in the last three decades, multi-view action recognition is, still, a less exploited field. This paper provides a comprehensive survey of multi-view human action recognition approaches. The approaches are reviewed following an application-based categorization: methods are categorized based on their ability to operate using a fixed or an arbitrary number of cameras. Finally, benchmark databases frequently used for evaluation of multi-view approaches are briefly described.
Keywords
cameras; image recognition; application-based categorization; cameras; multiview human action recognition; single-view human action recognition; Biological system modeling; Cameras; Databases; Shape; Solid modeling; Three-dimensional displays; Visualization; Multi-view action recognition; review; survey;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Hiding and Multimedia Signal Processing, 2013 Ninth International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/IIH-MSP.2013.135
Filename
6846691
Link To Document