Please use this identifier to cite or link to this item:
|Title:||Attentive behavior detection by non-linear head pose embedding and mapping||Authors:||Nan, H.
|Issue Date:||2006||Citation:||Nan, H.,Weimin, H.,Ranganath, S. (2006). Attentive behavior detection by non-linear head pose embedding and mapping. 2005 IEEE 7th Workshop on Multimedia Signal Processing : -. ScholarBank@NUS Repository. https://doi.org/10.1109/MMSP.2005.248585||Abstract:||In this paper, we present a new scheme to robustly detect a human attentive behavior, i.e., a frequent change in focus of attention (FCFA) from video sequences. The FCFA behavior can be easily perceived by people as temporal changes of human head pose. Here, we propose a non-linear head pose embedding and mapping algorithm to detect the pose in each frame of the sequence. Developed from ISOMAP, we learn a person-independent and non-linear embedding space (we call it a 2-D feature space) for different head poses. A non-linear interpolation mapping followed by an adaptive local fitting method is designed to map new frames into the 2-D feature space where head poses can be further obtained. An entropy classifier is then proposed on each sequence to detect the FCFA behavior. Experiments reported in this paper showed robust results.||Source Title:||2005 IEEE 7th Workshop on Multimedia Signal Processing||URI:||http://scholarbank.nus.edu.sg/handle/10635/69459||ISBN:||0780392892||DOI:||10.1109/MMSP.2005.248585|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Sep 11, 2019
checked on Sep 8, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.