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
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;
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing, 2013 Ninth International Conference on
Conference_Location :
Beijing
DOI :
10.1109/IIH-MSP.2013.135