DocumentCode :
80231
Title :
Cognitive emotion model for eldercare robot in smart home
Author :
Han Jing ; Xie Lun ; Li Dan ; He Zhijie ; Wang Zhiliang
Author_Institution :
Sch. of Comput. & Commun. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
Volume :
12
Issue :
4
fYear :
2015
fDate :
Apr-15
Firstpage :
32
Lastpage :
41
Abstract :
Based on the smart home and facial expression recognition, this paper presents a cognitive emotional model for eldercare robot. By combining with Gabor filter, Local Binary Pattern algorithm (LBP) and k-Nearest Neighbor algorithm (KNN) are facial emotional features extracted and recognized. Meanwhile, facial emotional features put influence on robot´s emotion state, which is described in AVS emotion space. Then the optimization of smart home environment on the cognitive emotional model is specially analyzed using simulated annealing algorithm (SA). Finally, transition probability from any emotional state to a state of basic emotions is obtained based on the cognitive reappraisal strategy and Euclidean distance. The simulation and experiment have tested and verified the effective in reducing negative emotional state.
Keywords :
Gabor filters; control engineering computing; emotion recognition; face recognition; feature extraction; geriatrics; medical robotics; probability; robot vision; simulated annealing; AVS emotion space; Euclidean distance; Gabor filter; KNN; LBP; SA; cognitive emotion model; cognitive reappraisal strategy; eldercare robot; emotional state; facial emotional feature extraction; facial expression recognition; k-nearest neighbor algorithm; local binary pattern algorithm; negative emotional state reduction; simulated annealing algorithm; smart home; transition probability; Analytical models; Computational modeling; Emotion recognition; Mouth; Robots; Senior citizens; Smart homes; AVS emotion space; cognitive emotion model; eldercare robot; emotional state transition; expression recognition; smart home;
fLanguage :
English
Journal_Title :
Communications, China
Publisher :
ieee
ISSN :
1673-5447
Type :
jour
DOI :
10.1109/CC.2015.7114067
Filename :
7114067
Link To Document :
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