Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/70300
Title: Fast detection of frequent change in focus of human attention
Authors: Hu, N.
Huang, W.
Ranganath, S. 
Issue Date: 2005
Source: Hu, N.,Huang, W.,Ranganath, S. (2005). Fast detection of frequent change in focus of human attention. Lecture Notes in Computer Science 3368 : 216-230. ScholarBank@NUS Repository.
Abstract: We present an algorithm to detect the attentive behavior of persons with frequent change in focus of attention (FCFA) from a static video camera. This behavior can be easily perceived by people as temporal changes of human head pose. Here, we propose to use features extracted by analyzing a similarity matrix of head pose by using a self-similarity measure of the head image sequence. Further, we present a fast algorithm which uses an image vector sequence represented in the principal components subspace instead of the original image sequence to measure the self-similarity. An important feature of the behavior of FCFA is its cyclic pattern where the head pose repeats its position from time to time. A frequency analysis scheme is proposed to find the dynamic characteristics of persons with frequent change of attention or focused attention. A nonparametric classifier is used to classify these two kinds of behaviors (FCFA and focused attention). The fast algorithm discussed in this paper yields real-time performance as well as good accuracy. © Springer-Verlag Berlin Heidelberg 2005.
Source Title: Lecture Notes in Computer Science
URI: http://scholarbank.nus.edu.sg/handle/10635/70300
ISSN: 03029743
Appears in Collections:Staff Publications

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