DocumentCode
3086843
Title
Automatic understanding of human behavior in videos: A review
Author
Bouzegza, Mourad ; Elarbi-Boudihir, M.
Author_Institution
Coll. of Comput. Sci., Imam Univ., Riyadh, United Arab Emirates
fYear
2013
fDate
12-15 May 2013
Firstpage
185
Lastpage
190
Abstract
Real-time understanding of human behavior in video streams is presently one of the most active areas of research in Computer Vision and Artificial Intelligence. Its purpose is to automatically detect, track and describe human activities in a sequence of image frames. Challenges in this topic of research are numerous and sometimes very difficult to work out. Consequently, the progress is very slow and the results are not very satisfactory. This paper aims to survey the methods used in human behavior understanding, showing their strengths and weaknesses. This small “toolbox” of methods and strategies could be very useful to the researcher and the engineer alike.
Keywords
behavioural sciences; computer vision; image sequences; video signal processing; video streaming; artificial intelligence; automatic human behavior understanding; computer vision; human activities; image frame sequence; real-time human behavior understanding; video streams; Computational modeling; Computer vision; Grammar; Hidden Markov models; Taxonomy; Tracking; Videos; abnormal human behavior; behavior understanding; computer vision; surveillance;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on
Conference_Location
Algiers
Type
conf
DOI
10.1109/WoSSPA.2013.6602359
Filename
6602359
Link To Document