A Facial Expression Recognition Approach for Social IoT Frameworks

Akkaş, 2020, Healthcare and patient monitoring using iot, Int. Things, 11 Alam, 2019, Healthcare iot-based affective state mining using a deep convolutional neural network, IEEE Access, 7, 75189, 10.1109/ACCESS.2019.2919995 An, 2015, Efficient smile detection by extreme learning machine, Neurocomputing, 149, 354, 10.1016/j.neucom.2014.04.072 Atzori, 2014, From “smart objects” to “social objects”: the next evolutionary step of the internet of things, IEEE Commun. Mag., 52, 97, 10.1109/MCOM.2014.6710070 Atzori, 2012, The social internet of things (siot)–when social networks meet the internet of things: concept, architecture and network characterization, Comput. Netw., 56, 3594, 10.1016/j.comnet.2012.07.010 Avila, 2013 Baker, 2017, Internet of things for smart healthcare: technologies, challenges, and opportunities, IEEE Access, 5, 26521, 10.1109/ACCESS.2017.2775180 Bartlett, 2005, Recognizing facial expression: machine learning and application to spontaneous behavior, 568 Bisogni, 2022, Impact of deep learning approaches on facial expression recognition in healthcare industries, IEEE Trans. Ind. Inform., 18, 5619, 10.1109/TII.2022.3141400 Calvo, 2010, Affect detection: an interdisciplinary review of models, methods, and their applications, IEEE Trans. Affect. Comput., 1, 18, 10.1109/T-AFFC.2010.1 Canedo, 2019, Facial expression recognition using computer vision: a systematic review, Appl. Sci., 9, 4678, 10.3390/app9214678 Chambers, 2012, Social network analysis in healthcare settings: a systematic scoping review, PLoS ONE, 7, 10.1371/journal.pone.0041911 Chen, 2016, Facial expression recognition with dynamic gabor volume feature, 1 Cohn, 2002, Individual differences in facial expression: stability over time, relation to self-reported emotion, and ability to inform person identification, 491 Colmenarez, 1997, Face detection with information-based maximum discrimination, 782 Corneanu, 2016, Survey on rgb, 3d, thermal, and multimodal approaches for facial expression recognition: history, trends, and affect-related applications, IEEE Trans. Pattern Anal. Mach. Intell., 38, 1548, 10.1109/TPAMI.2016.2515606 Darwin, 1998 Dudani, 1976, The distance-weighted k-nearest-neighbor rule, IEEE Trans. Syst. Man Cybern., 325, 10.1109/TSMC.1976.5408784 Ekman, 1982, Methods for Measuring Facial Action, 45 Ekman, 1971, Constants across cultures in the face and emotion, J. Pers. Soc. Psychol., 17, 124, 10.1037/h0030377 Gachet Páez, 2018, Healthy and wellbeing activities' promotion using a big data approach, Health Inform. J., 24, 125, 10.1177/1460458216660754 Guerrero-Ibanez, 2015, Integration challenges of intelligent transportation systems with connected vehicle, cloud computing, and internet of things technologies, IEEE Wirel. Commun., 22, 122, 10.1109/MWC.2015.7368833 Gupta, 2020, An overview of internet of things (iot): architectural aspects, challenges, and protocols, Concurr. Comput., Pract. Exp., 32, 10.1002/cpe.4946 A. Hassan, R.I. Damper, Multi-class and hierarchical svms for emotion recognition, 2010. Holmquist, 2001, Smart-its friends: a technique for users to easily establish connections between smart artefacts, 116 Hossain, 2021, A unified framework of deep learning-based facial expression recognition system for diversified applications, Appl. Sci., 11, 9174, 10.3390/app11199174 Jones, 2002, Statistical color models with application to skin detection, Int. J. Comput. Vis., 46, 81, 10.1023/A:1013200319198 Kang, 2017, Intelligent personal health devices converged with internet of things networks, J. Mob. Multimed., 12, 197 Kumar, 2014, A detailed review of feature extraction in image processing systems, 5 Lakkis, 2017, Iot based emergency and operational services in medical care systems, 1 Lazebnik, 2006, Beyond bags of features: spatial pyramid matching for recognizing natural scene categories, 2169 Liu, 2016, Facial expression recognition with pca and lbp features extracting from active facial patches, 368 Lucey, 2010, The extended cohn-kanade dataset (ck+): a complete dataset for action unit and emotion-specified expression, 94 Lyons, 1998, Coding facial expressions with gabor wavelets, 200 Lyons, 1999, Automatic classification of single facial images, IEEE Trans. Pattern Anal. Mach. Intell., 21, 1357, 10.1109/34.817413 Mano, 2016, Exploiting iot technologies for enhancing health smart homes through patient identification and emotion recognition, Comput. Commun., 89, 178, 10.1016/j.comcom.2016.03.010 Marcos, 2011, Nonverbal communication with a multimodal agent via facial expression recognition, 1199 Martinez, 2016, Advances, challenges, and opportunities in automatic facial expression recognition, 63 Matthews, 2004, Active appearance models revisited, Int. J. Comput. Vis., 60, 135, 10.1023/B:VISI.0000029666.37597.d3 Mehrabian, 2017 Mollahosseini, 2016, Going deeper in facial expression recognition using deep neural networks, 1 Ng, 2002, On discriminative vs. generative classifiers: a comparison of logistic regression and naive bayes, 841 Nitti, 2014, Friendship selection in the social internet of things: challenges and possible strategies, IEEE Int. Things J., 2, 240, 10.1109/JIOT.2014.2384734 Pantic, 2000, Automatic analysis of facial expressions: the state of the art, IEEE Trans. Pattern Anal. Mach. Intell., 22, 1424, 10.1109/34.895976 Rao, 2015, Multi-pose facial expression recognition based on surf boosting, 630 Rashidi, 2010, Discovering activities to recognize and track in a smart environment, IEEE Trans. Knowl. Data Eng., 23, 527, 10.1109/TKDE.2010.148 Rivera, 2012, Local directional number pattern for face analysis: face and expression recognition, IEEE Trans. Image Process., 22, 1740, 10.1109/TIP.2012.2235848 Roopa, 2019, Social internet of things (siot): foundations, thrust areas, systematic review and future directions, Comput. Commun., 139, 32, 10.1016/j.comcom.2019.03.009 Rose, 2006, Facial expression classification using gabor and log-gabor filters, 346 Safavian, 1991, A survey of decision tree classifier methodology, IEEE Trans. Syst. Man Cybern., 21, 660, 10.1109/21.97458 Saheb, 2019, Paradigm of iot big data analytics in the healthcare industry: a review of scientific literature and mapping of research trends, Telemat. Inform., 41, 70, 10.1016/j.tele.2019.03.005 Salih Juboori, 2021, Designing the iot based social distancing monitoring system for reducing the impact of covid-19, Ilkogr. Online, 20 Shojaeilangari, 2011, Person independent facial expression analysis using gabor features and genetic algorithm, 1 Simonyan Sonka, 2014 Stojkoska, 2017, A review of internet of things for smart home: challenges and solutions, J. Clean. Prod., 140, 1454, 10.1016/j.jclepro.2016.10.006 Szegedy, 2017, Inception-v4, inception-resnet and the impact of residual connections on learning Szegedy, 2016, Rethinking the inception architecture for computer vision, 2818 Tian, 2001, Recognizing action units for facial expression analysis, IEEE Trans. Pattern Anal. Mach. Intell., 23, 97, 10.1109/34.908962 Vahdat-Nejad, 2020, Social internet of things and new generation computing—a survey, 139 Valenti, 2010, Sonify your face: facial expressions for sound generation, 1363 Valero, 2022, Ebasi: iot-based emotion and behaviour recognition system against elderly people social isolation, 3 Valstar, 2011, The first facial expression recognition and analysis challenge, 921 Vupputuri, 2015, Facial expression recognition using local binary patterns and kullback leibler divergence, 0349 Wang, 2010, Locality-constrained linear coding for image classification, 3360 Wu, 2010, Facial expression recognition using gabor motion energy filters, 42 Yang, 2016, Effective face recognition using bag of features with additive kernels, J. Electron. Imaging, 25, 10.1117/1.JEI.25.1.013025 Yoo, 2018, Mining-based lifecare recommendation using peer-to-peer dataset and adaptive decision feedback, Peer Peer Netw. Appl., 11, 1309, 10.1007/s12083-017-0620-2 Zavarez, 2017, Cross-database facial expression recognition based on fine-tuned deep convolutional network, 405 Zavaschi, 2013, Fusion of feature sets and classifiers for facial expression recognition, Expert Syst. Appl., 40, 646, 10.1016/j.eswa.2012.07.074 Zeng, 2009, A survey of affect recognition methods: audio, visual, and spontaneous expressions, IEEE Trans. Pattern Anal. Mach. Intell., 31, 39, 10.1109/TPAMI.2008.52 Zhang, 1998, Comparison between geometry-based and gabor-wavelets-based facial expression recognition using multi-layer perceptron, 454