Recognition of human emotion transition from video sequence using triangulation induced various centre pairs distance signatures

Applied Soft Computing - Tập 134 - Trang 109971 - 2023
Md Nasir1, Paramartha Dutta1, Avishek Nandi1
1Department of Computer & System Sciences, Visva-Bharati University, Santiniketan, 731235, India

Tài liệu tham khảo

López-Gil, 2021, Photogram classification-based emotion recognition, IEEE Access, 9, 136974, 10.1109/ACCESS.2021.3117253 Cohen, 2002, Facial expression recognition from video sequences, Vol. 2, 121 Mehrabian, 2008, Communication without words, Commun. Theory, 193 Ko, 2018, A brief review of facial emotion recognition based on visual information, Sensors, 18, 401, 10.3390/s18020401 Duncan, 2016 Ekman, 1997, Universal facial expressions of emotion, 27 Ekman, 1971, Constants across cultures in the face and emotion, J. Personal. Soc. Psychol., 17, 124, 10.1037/h0030377 Park, 2021, A robust facial expression recognition algorithm based on multi-rate feature fusion scheme, Sensors, 21, 6954, 10.3390/s21216954 Dhuheir, 2021, Emotion recognition for healthcare surveillance systems using neural networks: A survey, 681 Bhattacharya, 2020, Smart home security system using emotion detection, Int. Res. J. Eng. Technol. (IRJET), 7 Bianco, 2021, A smart mirror for emotion monitoring in home environments, Sensors, 21, 7453, 10.3390/s21227453 Minaee, 2021, Deep-emotion: Facial expression recognition using attentional convolutional network, Sensors, 21, 3046, 10.3390/s21093046 Barman, 2021, Facial expression recognition using distance and shape signature features, Pattern Recognit. Lett., 145, 254, 10.1016/j.patrec.2017.06.018 Barman, 2017, Facial expression recognition using shape signature feature, 174 Barman, 2019, Facial expression recognition using distance and texture signature relevant features, Appl. Soft Comput., 77, 88, 10.1016/j.asoc.2019.01.011 Barman, 2019, Influence of shape and texture features on facial expression recognition, IET Image Process., 13, 1349, 10.1049/iet-ipr.2018.5481 Fang, 2014, Facial expression recognition in dynamic sequences: An integrated approach, Pattern Recognit., 47, 1271, 10.1016/j.patcog.2013.09.023 Zhao, 2017, Facial expression recognition from video sequences based on spatial-temporal motion local binary pattern and gabor multiorientation fusion histogram, Math. Probl. Eng., 2017 Ghimire, 2017, Facial expression recognition Using Local Region specific dense optical flow and LBP features, 28 Lucey, 2010, The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression, 94 Valstar, 2010, Induced disgust, happiness and surprise: an addition to the mmi facial expression database, 65 Aifanti, 2010, The MUG facial expression database, 1 G. Tzimiropoulos, M. Pantic, Optimization problems for fast aam fitting in-the-wild, in: Proceedings of the IEEE International Conference on Computer Vision, 2013, pp. 593–600. Ding, 2017, Facial expression recognition from image sequence based on LBP and taylor expansion, IEEE Access, 5, 19409, 10.1109/ACCESS.2017.2737821 Kotsia, 2006, Facial expression recognition in image sequences using geometric deformation features and support vector machines, IEEE Trans. Image Process., 16, 172, 10.1109/TIP.2006.884954 Santemiz, 2018, Automatic face recognition for home safety using video-based side-view face images, IET Biom., 7, 606, 10.1049/iet-bmt.2017.0203 Kumari, 2015, Facial expression recognition: A survey, Procedia Comput. Sci., 58, 486, 10.1016/j.procs.2015.08.011 Moore, 2011, Local binary patterns for multi-view facial expression recognition, Comput. Vis. Image Underst., 115, 541, 10.1016/j.cviu.2010.12.001 Shan, 2009, Facial expression recognition based on local binary patterns: A comprehensive study, Image Vis. Comput., 27, 803, 10.1016/j.imavis.2008.08.005 Zhao, 2007, Dynamic texture recognition using local binary patterns with an application to facial expressions, IEEE Trans. Pattern Anal. Mach. Intell., 29, 915, 10.1109/TPAMI.2007.1110 Zhao, 2011, Facial expression recognition based on local binary patterns and kernel discriminant isomap, Sensors, 11, 9573, 10.3390/s111009573 Zhang, 2012, Robust facial expression recognition via compressive sensing, Sensors, 12, 3747, 10.3390/s120303747 Ghimire, 2014, Extreme learning machine ensemble using bagging for facial expression recognition, JIPS, 10, 443 Sadeghi, 2013, Facial expression recognition using geometric normalization and appearance representation, 159 Mayer, 2010, Adjusted pixel features for robust facial component classification, Image Vis. Comput., 28, 762, 10.1016/j.imavis.2009.07.012 Tian, 2003, Real world real-time automatic recognition of facial expressions Kobayashi, 1992, Recognition of six basic facial expression and their strength by neural network, 381 Pai, 2011, An embedded system for real-time facial expression recognition based on the extension theory, Comput. Math. Appl., 61, 2101, 10.1016/j.camwa.2010.08.082 Liliana, 2016, Human emotion recognition based on active appearance model and semi-supervised fuzzy C-means, 439 Asthana, 2009, Evaluating AAM fitting methods for facial expression recognition, 1 Choi, 2006, Realtime facial expression recognition using active appearance model and multilayer perceptron, 5924 Ahn, 2012, Real-time facial landmarks tracking using active shape model and lk optical flow, 541 P. Michel, R. El Kaliouby, Real time facial expression recognition in video using support vector machines, in: Proceedings of the 5th International Conference on Multimodal Interfaces, 2003, pp. 258–264. Sohail, 2007, Classification of facial expressions using k-nearest neighbor classifier, 555 Meftah, 2012, Emotion recognition using KNN classification for user modeling and sharing of affect states, 234 Gu, 2012, Facial expression recognition using radial encoding of local Gabor features and classifier synthesis, Pattern Recognit., 45, 80, 10.1016/j.patcog.2011.05.006 Goyal, 2014, Facial expression recognition using artificial neural network, HCTL Open Int. J. Technol. Innov. Res., 10, 1 Haris Rismayana, 2018, Face expression recognition using artificial neural network (ANN) model back propagation, 126 Bejani, 2014, Audiovisual emotion recognition using ANOVA feature selection method and multi-classifier neural networks, Neural Comput. Appl., 24, 399, 10.1007/s00521-012-1228-3 Saroop, 2021 Mao, 2021 Yao, 2021, Real-time facial expression recognition system for video big sensor data security application, Secur. Commun. Netw., 2021, 10.1155/2021/9539022 Meng, 2019, Frame attention networks for facial expression recognition in videos, 3866 Abdulsalam, 2019, Facial emotion recognition from videos using deep convolutional neural networks, Int. J. Mach. Learn. Comput., 9, 14, 10.18178/ijmlc.2019.9.1.759 Saeed, 2014, Frame-based facial expression recognition using geometrical features, Adv. Hum.-Comput. Interact., 2014, 10.1155/2014/408953 Li, 2013, Simultaneous facial feature tracking and facial expression recognition, IEEE Trans. Image Process., 22, 2559, 10.1109/TIP.2013.2253477 Ghimire, 2017, Recognition of facial expressions based on salient geometric features and support vector machines, Multimedia Tools Appl., 76, 7921, 10.1007/s11042-016-3428-9 Yaddaden, 2017 Mohammadian, 2015, Video-based facial expression recognition by removing the style variations, IET Image Process., 9, 596, 10.1049/iet-ipr.2013.0697 Liu, 2020, Ga-svm-based facial emotion recognition using facial geometric features, IEEE Sens. J., 21, 11532, 10.1109/JSEN.2020.3028075 Ashir, 2020, Facial expression recognition with dynamic cascaded classifier, Neural Comput. Appl., 32, 6295, 10.1007/s00521-019-04138-4 Zhang, 2019, Learning affective video features for facial expression recognition via hybrid deep learning, IEEE Access, 7, 32297, 10.1109/ACCESS.2019.2901521 Majumder, 2014, Emotion recognition from geometric facial features using self-organizing map, Pattern Recognit., 47, 1282, 10.1016/j.patcog.2013.10.010 Cruz, 2014, Vision and attention theory based sampling for continuous facial emotion recognition, IEEE Trans. Affect. Comput., 5, 418, 10.1109/TAFFC.2014.2316151 Kim, 2017, Multi-objective based spatio-temporal feature representation learning robust to expression intensity variations for facial expression recognition, IEEE Trans. Affect. Comput., 10, 223, 10.1109/TAFFC.2017.2695999 Liu, 2014, Deeply learning deformable facial action parts model for dynamic expression analysis, 143 Wu, 2021, Facial expression recognition based on multi-features cooperative deep convolutional network, Appl. Sci., 11, 1428, 10.3390/app11041428 Jeong, 2020, Deep joint spatiotemporal network (DJSTN) for efficient facial expression recognition, Sensors, 20, 1936, 10.3390/s20071936 Rahulamathavan, 2012, Facial expression recognition in the encrypted domain based on local fisher discriminant analysis, IEEE Trans. Affect. Comput., 4, 83, 10.1109/T-AFFC.2012.33 Aifanti, 2014, Linear subspaces for facial expression recognition, Signal Process., Image Commun., 29, 177, 10.1016/j.image.2013.10.004 Rahulamathavan, 2015, Efficient privacy-preserving facial expression classification, IEEE Trans. Dependable Secure Comput., 14, 326