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
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;
Conference_Titel :
Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on
Conference_Location :
Algiers
DOI :
10.1109/WoSSPA.2013.6602359