Emotion Recognition System in Images Based On Fuzzy Neural Network and HMM Export

@inproceedings{citeulike:2861600, abstract = {An emotion recognition system based on neuro-HMM was proposed to analyze the emotion contained in images. This system took an initial step in this direction by describing a set of proposed difficulty metrics based on cognitive principles. Both the emotion semanteme extraction and emotion model construction were considered in this system. They were respectively carried out by neural networks and HMM. According to the strong relationship between image notable lines and human dynamism sensation, the system used fuzzy neural network to establish the mapping and obtained the image emotion semanteme sequence. Then the duple hidden Markov model (HMM) was employed to simulate human emotion transition and finally confirmed different emotion models. The system also considered some outer influences to make the system rules be refined in realistic conditions. The experiment shows at least one emotion from an image can be recognized. The results illustrate the capability of the developing image recognition system}, author = {Guo, Yimo and Gao, Huanping}, booktitle = {Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on}, citeulike-article-id = {2861600}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/COGINF.2006.365679}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4216394}, doi = {10.1109/COGINF.2006.365679}, journal = {Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on}, keywords = {emotion\_recognition, emotions, fuzzy\_logic, nn}, pages = {73--78}, posted-at = {2008-06-04 16:56:46}, priority = {2}, title = {Emotion Recognition System in Images Based On Fuzzy Neural Network and HMM}, url = {http://dx.doi.org/10.1109/COGINF.2006.365679}, volume = {1}, year = {2006} }

TY - CONF ID - citeulike:2861600 L3 - citeulike-article-id:2861600 N2 - An emotion recognition system based on neuro-HMM was proposed to analyze the emotion contained in images. This system took an initial step in this direction by describing a set of proposed difficulty metrics based on cognitive principles. Both the emotion semanteme extraction and emotion model construction were considered in this system. They were respectively carried out by neural networks and HMM. According to the strong relationship between image notable lines and human dynamism sensation, the system used fuzzy neural network to establish the mapping and obtained the image emotion semanteme sequence. Then the duple hidden Markov model (HMM) was employed to simulate human emotion transition and finally confirmed different emotion models. The system also considered some outer influences to make the system rules be refined in realistic conditions. The experiment shows at least one emotion from an image can be recognized. The results illustrate the capability of the developing image recognition system JF - Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on EP - 78 TI - Emotion Recognition System in Images Based On Fuzzy Neural Network and HMM VL - 1 T2 - Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on SP - 73 KW - emotion_recognition KW - emotions KW - fuzzy_logic KW - nn AU - Guo, Yimo AU - Gao, Huanping PY - 2006/// UR - http://dx.doi.org/10.1109/COGINF.2006.365679 ER -