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Relevant bibliographies by topics / Facial expression processing

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Academic literature on the topic 'Facial expression processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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Journal articles on the topic "Facial expression processing"

1

Young, A. W. "Facial expression processing after amygdalotomy." Neurocase 3, no. 4 (1997): 267j—274. http://dx.doi.org/10.1093/neucas/3.4.267-j.

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Young, Andrew W., Deborah J. Hellawell, Claudia Van de Wal, and Michael Johnson. "Facial expression processing after amygdalotomy." Neuropsychologia 34, no. 1 (1996): 31–39. http://dx.doi.org/10.1016/0028-3932(95)00062-3.

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Bondarenko, Yakov A., and Galina Ya Menshikova. "EXPLORING ANALYTICAL AND HOLISTIC PROCESSING IN FACIAL EXPRESSION RECOGNITION." Moscow University Psychology Bulletin, no. 2 (2020): 103–40. http://dx.doi.org/10.11621/vsp.2020.02.06.

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Background. The study explores two main processes of perception of facial expression: analytical (perception based on individual facial features) and holistic (holistic and non-additive perception of all features). The relative contribution of each process to facial expression recognition is still an open question. Objective. To identify the role of holistic and analytical mechanisms in the process of facial expression recognition. Methods. A method was developed and tested for studying analytical and holistic processes in the task of evaluating subjective differences of expressions, using com

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Kuehne, Maria, Isabelle Siwy, Tino Zaehle, Hans-Jochen Heinze, and Janek S. Lobmaier. "Out of Focus: Facial Feedback Manipulation Modulates Automatic Processing of Unattended Emotional Faces." Journal of Cognitive Neuroscience 31, no. 11 (2019): 1631–40. http://dx.doi.org/10.1162/jocn_a_01445.

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Facial expressions provide information about an individual's intentions and emotions and are thus an important medium for nonverbal communication. Theories of embodied cognition assume that facial mimicry and resulting facial feedback plays an important role in the perception of facial emotional expressions. Although behavioral and electrophysiological studies have confirmed the influence of facial feedback on the perception of facial emotional expressions, the influence of facial feedback on the automatic processing of such stimuli is largely unexplored. The automatic processing of unattended

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Garrido, L., and B. Duchaine. "Do facial identity and facial expression processing dissociate in prosopagnosia?" Journal of Vision 7, no. 9 (2010): 939. http://dx.doi.org/10.1167/7.9.939.

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Bell, Lauren, and Tirta Susilo. "Facial identity and facial expression processing dissociate in developmental prosopagnosia." Journal of Vision 18, no. 10 (2018): 918. http://dx.doi.org/10.1167/18.10.918.

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XIA, Mu, Xueliu LI, Chun YE, and Hong LI. "The ERPs for the Facial Expression Processing." Advances in Psychological Science 22, no. 10 (2014): 1556. http://dx.doi.org/10.3724/sp.j.1042.2014.01556.

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Vigil, Jacob M., and Patrick Coulombe. "Embodied simulation and the search for meaning are not necessary for facial expression processing." Behavioral and Brain Sciences 33, no. 6 (2010): 461–63. http://dx.doi.org/10.1017/s0140525x10001603.

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AbstractEmbodied simulation and the epistemic motivation to search for the “meaning” of other people's behaviors are not necessary for specific and functional responding to, and hence processing of, human facial expressions. Rather, facial expression processing can be achieved through lower-cognitive, heuristical perceptual processing and expression of prototypical morphological musculature movement patterns that communicate discrete trustworthiness and capacity cues to conspecifics.

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Matsumiya, Kazumichi. "Retinotopy of Facial Expression Adaptation." Multisensory Research 27, no. 2 (2014): 127–37. http://dx.doi.org/10.1163/22134808-00002446.

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The face aftereffect (FAE; the illusion of faces after adaptation to a face) has been reported to occur without retinal overlap between adaptor and test, but recent studies revealed that the FAE is not constant across all test locations, which suggests that the FAE is also retinotopic. However, it remains unclear whether the characteristic of the retinotopy of the FAE for one facial aspect is the same as that of the FAE for another facial aspect. In the research reported here, an examination of the retinotopy of the FAE for facial expression indicated that the facial expression aftereffect occ

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Padmapriya K.C., Leelavathy V., and Angelin Gladston. "Automatic Multiface Expression Recognition Using Convolutional Neural Network." International Journal of Artificial Intelligence and Machine Learning 11, no. 2 (2021): 1–13. http://dx.doi.org/10.4018/ijaiml.20210701.oa8.

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The human facial expressions convey a lot of information visually. Facial expression recognition plays a crucial role in the area of human-machine interaction. Automatic facial expression recognition system has many applications in human behavior understanding, detection of mental disorders and synthetic human expressions. Recognition of facial expression by computer with high recognition rate is still a challenging task. Most of the methods utilized in the literature for the automatic facial expression recognition systems are based on geometry and appearance. Facial expression recognition is

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Dissertations / Theses on the topic "Facial expression processing"

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Hattiangadi, Nina Uday. "Facial affect processing across a perceptual timeline : a comparison of two models of facial affect processing /." Full text (PDF) from UMI/Dissertation Abstracts International, 2000. http://wwwlib.umi.com/cr/utexas/fullcit?p3004278.

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Shang, Lifeng, and 尚利峰. "Facial expression analysis with graphical models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B47849484.

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Facial expression recognition has become an active research topic in recent years due to its applications in human computer interfaces and data-driven animation. In this thesis, we focus on the problem of how to e?ectively use domain, temporal and categorical information of facial expressions to help computer understand human emotions. Over the past decades, many techniques (such as neural networks, Gaussian processes, support vector machines, etc.) have been applied to facial expression analysis. Recently graphical models have emerged as a general framework for applying probabilistic mo

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Kaufmann, Jurgen Michael. "Interactions between the processing of facial identity, emotional expression and facial speech." Thesis, University of Glasgow, 2002. http://theses.gla.ac.uk/3110/.

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The experiments investigate the functional relationship between the processing of facial identity, emotional expression and facial speech. They were designed in order to further explore a widely accepted model of parallel, independent face perception components (Bruce and Young, 1986), which has been challenged recently (e.g. Walker et. al., 1995; Yakel et. al., 2000; Schweinberger et. al., 1998; Schweinberger et.al., 1999). In addition to applying a selective attention paradigm (Garner, 1974; 1976), dependencies between face related processes are explored by morphing, a digital graphic editin

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Walker, Stephanie. "Processing information in the human face : evidence from dynamic stimuli." Thesis, University of Nottingham, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363606.

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Hoag, David Nelson. "Facial Expression Decoding Deficits Among Psychiatric Patients: Attention, Encoding, and Processing." Thesis, North Texas State University, 1988. https://digital.library.unt.edu/ark:/67531/metadc330648/.

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Psychiatric patients, particularly schizophrenics, tend to be less accurate decoders of facial expressions than normals. The involvement of three basic information processing stages in this deficit was investigated: attention; encoding; and processing. Psychiatric inpatients, classified by diagnosis and severity of pathology, and nonpatient controls were administered seven facial cue decoding tasks. Orientation of attention was assessed through rate of diversion of gaze from the stimuli. Encoding was assessed using simple tasks, requiring one contrast of two facial stimuli and selection from t

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Wong, Ka-wai Teresa. "Event-related potential analysis of facial emotion processing." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/HKUTO/record/B3955773X.

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Wong, Ka-wai Teresa, and 黃嘉慧. "Event-related potential analysis of facial emotion processing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B3955773X.

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Yan, Xiaoqian. "Cultural similarities and differences in facial identity and expression processing." Thesis, University of York, 2016. http://etheses.whiterose.ac.uk/14333/.

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A range of research has shown an advantage for the perception of faces from same-race compared to other-races – the other race effect (ORE). Nevertheless, previous studies have focused on the ability to recognize facial identity. This thesis focuses on how information from the face that conveys expression is processed in own-race and other-race faces. First, the cross-cultural processing of facial expressions of basic emotions in Western Caucasian and Chinese observers was investigated. Perceptual judgments of facial expressions were quite similar between cultural groups, but facial expression

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Le, Gal Patricia Margaret. "Cognitive aspects of emotional expression processing." Thesis, University of Stirling, 1999. http://hdl.handle.net/1893/1772.

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This thesis investigates the hypothesis that emotions play an influential role in cognition. Interference between facial emotional expression processing and selected tasks is measured using a variety of experimental methods. Prior to the main experimental chapters, the collection and assessment (Chapter 2, Exp. 1) of stimulus materials is described. Experiments 2-11 then concentrate on the likelihood of interference with other types of information from the face. Findings using a Garner design suggest that, although identity processing may be independent of expression variation, expression proc

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Kokin, Jessica. "Facial Expression Recognition and Interpretation in Shy Children." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32079.

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Two studies were conducted in which we examined the relation between shyness and facial expression processing in children. In Study 1, facial expression recognition was examined by asking 97 children ages 12 to 14 years to identify six different expressions displayed at 50% and 100% intensity, as well as a neutral expression. In Study 2, the focus shifted from the recognition of emotions to the interpretation of emotions. In this study, 123 children aged 12 to 14 years were asked a series of questions regarding how they would perceive different facial expressions. Findings from Study 1 showed

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Books on the topic "Facial expression processing"

1

Darris, Dobbs, ed. Animating facial features and expression. Charles River Media, 1999.

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Hadyn, Ellis, and North Atlantic Treaty Organization. Scientific Affairs Division., eds. Aspects of face processing. M. Nijhoff, 1986.

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Niedenthal, Paula M., Adrienne Wood, Magdalena Rychlowska, and Sebastian Korb. Embodied Simulation in Decoding Facial Expression. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190613501.003.0021.

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The present chapter explores evidence for the role of embodied simulation and facial mimicry in the decoding of facial expression of emotion. We begin the chapter by reviewing evidence in favor of the hypothesis that mimicking a perceived facial expression helps the perceiver achieve greater decoding accuracy. We report experimental and correlational evidence in favor of the general effect, and we also examine the assertion that facial mimicry influences perceptual processing of facial expression. Finally, after examining the behavioral evidence, we look into the brain to explore the neural ci

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Dobbs, Darris, and Bill Fleming. Animating Facial Features & Expressions. Charles River Media, 1998.

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Social Signal Processing. Cambridge University Press, 2017.

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Aspects of Face Processing (Nato Science Series D:). Springer, 1986.

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S, Pandzic Igor, and Forchheimer Robert, eds. MPEG-4 facial animation: The standard, implementation and applications. J. Wiley, 2002.

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Forchheimer, Robert, and Igor S. Pandzic. MPEG-4 Facial Animation: The Standard, Implementation and Applications. Wiley & Sons, Incorporated, John, 2007.

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Forchheimer, Robert, and Igor S. Pandzic. MPEG-4 Facial Animation: The Standard, Implementation and Applications. Wiley & Sons, Incorporated, John, 2003.

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(Editor), Igor S. Pandzic, and Robert Forchheimer (Editor), eds. MPEG-4 Facial Animation: The Standard, Implementation and Applications. Wiley, 2002.

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Book chapters on the topic "Facial expression processing"

1

Frijda, N. H. "Facial Expression Processing." In Aspects of Face Processing. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4420-6_34.

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Saha, Ashirbani, and Q. M. Jonathan Wu. "Curvelet Entropy for Facial Expression Recognition." In Advances in Multimedia Information Processing - PCM 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15696-0_57.

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Theng, Lau Bee. "Gabor Neural Network Based Facial Expression Recognition for Assistive Speech Expression." In Advances in Neuro-Information Processing. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03040-6_72.

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Chien, Chien-Chia, Yao-Jen Chang, and Yung-Chang Chen. "Facial Expression Analysis under Various Head Poses." In Advances in Multimedia Information Processing — PCM 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36228-2_148.

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Boughrara, Hayet, Liming Chen, Chokri Ben Amar, and Mohamed Chtourou. "Facial Expression Recognition Based on Perceived Facial Images and Local Feature Matching." In Image Analysis and Processing – ICIAP 2013. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41184-7_60.

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Salzen, E. A., E. A. Kostek, and D. J. Beavan. "The Perception of Action Versus Feeling in Facial Expression." In Aspects of Face Processing. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4420-6_35.

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Potter, D. D., and D. M. Parker. "Electrophysiological Correlates of Facial Identity and Expression Processing." In Developments in Clinical and Experimental Neuropsychology. Springer US, 1989. http://dx.doi.org/10.1007/978-1-4757-9996-5_12.

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Kamble, Kiran, Swapnil Sontakke, Pooja Mundada, and Apurva Pawar. "Threat Detection with Facial Expression and Suspicious Weapon." In Applied Computer Vision and Image Processing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4029-5_39.

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D’Ambrosio, Roberto, Giulio Iannello, and Paolo Soda. "Automatic Facial Expression Recognition Using Statistical-Like Moments." In Image Analysis and Processing – ICIAP 2011. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24085-0_60.

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Raouzaiou, Amaryllis, Spiros Ioannou, Kostas Karpouzis, Nicolas Tsapatsoulis, Stefanos Kollias, and Roddy Cowie. "An Intelligent Scheme for Facial Expression Recognition." In Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44989-2_132.

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Conference papers on the topic "Facial expression processing"

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Kulkarni, Ketki R., and Sahebrao B. Bagal. "Facial expression recognition." In 2015 International Conference on Information Processing (ICIP). IEEE, 2015. http://dx.doi.org/10.1109/infop.2015.7489442.

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Engin, Deniz, Hazim Kemal Ekenel, and Bilgisayar Muhendisligi Bolumu. "Facial expression pair matching." In 2017 25th Signal Processing and Communications Applications Conference (SIU). IEEE, 2017. http://dx.doi.org/10.1109/siu.2017.7960646.

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Kyperountas, Marios, Anastasios Tefas, and Ioannis Pitas. "Pairwise facial expression classification." In 2009 IEEE International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2009. http://dx.doi.org/10.1109/mmsp.2009.5293334.

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Tang, Hao, Wei Wang, Songsong Wu, et al. "Expression Conditional Gan for Facial Expression-to-Expression Translation." In 2019 IEEE International Conference on Image Processing (ICIP). IEEE, 2019. http://dx.doi.org/10.1109/icip.2019.8803654.

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Melaugh, Ryan, Nazmul Siddique, Sonya Coleman, and Pratheepan Yogarajah. "Facial Expression Recognition on partial facial sections." In 2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA). IEEE, 2019. http://dx.doi.org/10.1109/ispa.2019.8868630.

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Chen, Yuedong, Jianfeng Wang, Shikai Chen, Zhongchao Shi, and Jianfei Cai. "Facial Motion Prior Networks for Facial Expression Recognition." In 2019 IEEE Visual Communications and Image Processing (VCIP). IEEE, 2019. http://dx.doi.org/10.1109/vcip47243.2019.8965826.

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"Session: Facial Expression Understanding." In 2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP). IEEE, 2019. http://dx.doi.org/10.1109/iccp48234.2019.8959631.

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Liu, Wei-feng, Ji-li Lu, Zeng-fu Wang, and Hua-jun Song. "An Expression Space Model for Facial Expression Analysis." In 2008 Congress on Image and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/cisp.2008.216.

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Khanam, Assia, M. Zubair Shafiq, and M. Usman Akram. "Fuzzy Based Facial Expression Recognition." In 2008 Congress on Image and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/cisp.2008.694.

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"Application Authentication: Facial Expression Password." In International Conference Image Processing, Computers and Industrial Engineering. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e0114572.

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