Compound facial expressions of emotion
Understanding the different categories of facial expressions of emotion regularly used by us is essential to gain insights into human cognition and affect as well as for the design of computational models and perceptual interfaces. Past research on facial expressions of emotion has focused on the st...
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| Published in | Proceedings of the National Academy of Sciences - PNAS Vol. 111; no. 15; pp. E1454 - E1462 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
National Academy of Sciences
15.04.2014
National Acad Sciences |
| Series | PNAS Plus |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Understanding the different categories of facial expressions of emotion regularly used by us is essential to gain insights into human cognition and affect as well as for the design of computational models and perceptual interfaces. Past research on facial expressions of emotion has focused on the study of six basic categories—happiness, surprise, anger, sadness, fear, and disgust. However, many more facial expressions of emotion exist and are used regularly by humans. This paper describes an important group of expressions, which we call compound emotion categories. Compound emotions are those that can be constructed by combining basic component categories to create new ones. For instance, happily surprised and angrily surprised are two distinct compound emotion categories. The present work defines 21 distinct emotion categories. Sample images of their facial expressions were collected from 230 human subjects. A Facial Action Coding System analysis shows the production of these 21 categories is different but consistent with the subordinate categories they represent (e.g., a happily surprised expression combines muscle movements observed in happiness and surprised). We show that these differences are sufficient to distinguish between the 21 defined categories. We then use a computational model of face perception to demonstrate that most of these categories are also visually discriminable from one another. |
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| AbstractList | Though people regularly recognize many distinct emotions, for the most part, research studies have been limited to six basic categories—happiness, surprise, sadness, anger, fear, and disgust; the reason for this is grounded in the assumption that only these six categories are differentially represented by our cognitive and social systems. The results reported herein propound otherwise, suggesting that a larger number of categories is used by humans.
Understanding the different categories of facial expressions of emotion regularly used by us is essential to gain insights into human cognition and affect as well as for the design of computational models and perceptual interfaces. Past research on facial expressions of emotion has focused on the study of six basic categories—happiness, surprise, anger, sadness, fear, and disgust. However, many more facial expressions of emotion exist and are used regularly by humans. This paper describes an important group of expressions, which we call compound emotion categories. Compound emotions are those that can be constructed by combining basic component categories to create new ones. For instance, happily surprised and angrily surprised are two distinct compound emotion categories. The present work defines 21 distinct emotion categories. Sample images of their facial expressions were collected from 230 human subjects. A Facial Action Coding System analysis shows the production of these 21 categories is different but consistent with the subordinate categories they represent (e.g., a happily surprised expression combines muscle movements observed in happiness and surprised). We show that these differences are sufficient to distinguish between the 21 defined categories. We then use a computational model of face perception to demonstrate that most of these categories are also visually discriminable from one another. Understanding the different categories of facial expressions of emotion regularly used by us is essential to gain insights into human cognition and affect as well as for the design of computational models and perceptual interfaces. Past research on facial expressions of emotion has focused on the study of six basic categories -- happiness, surprise, anger, sadness, fear, and disgust. However, many more facial expressions of emotion exist and are used regularly by humans. This paper describes an important group of expressions, which we call compound emotion categories. Compound emotions are those that can be constructed by combining basic component categories to create new ones. For instance, happily surprised and angrily surprised are two distinct compound emotion categories. The present work defines 21 distinct emotion categories. Sample images of their facial expressions were collected from 230 human subjects. A Facial Action Coding System analysis shows the production of these 21 categories is different but consistent with the subordinate categories they represent (e.g., a happily surprised expression combines muscle movements observed in happiness and surprised). We show that these differences are sufficient to distinguish between the 21 defined categories. We then use a computational model of face perception to demonstrate that most of these categories are also visually discriminable from one another. [PUBLICATION ABSTRACT] Understanding the different categories of facial expressions of emotion regularly used by us is essential to gain insights into human cognition and affect as well as for the design of computational models and perceptual interfaces. Past research on facial expressions of emotion has focused on the study of six basic categories--happiness, surprise, anger, sadness, fear, and disgust. However, many more facial expressions of emotion exist and are used regularly by humans. This paper describes an important group of expressions, which we call compound emotion categories. Compound emotions are those that can be constructed by combining basic component categories to create new ones. For instance, happily surprised and angrily surprised are two distinct compound emotion categories. The present work defines 21 distinct emotion categories. Sample images of their facial expressions were collected from 230 human subjects. A Facial Action Coding System analysis shows the production of these 21 categories is different but consistent with the subordinate categories they represent (e.g., a happily surprised expression combines muscle movements observed in happiness and surprised). We show that these differences are sufficient to distinguish between the 21 defined categories. We then use a computational model of face perception to demonstrate that most of these categories are also visually discriminable from one another.Understanding the different categories of facial expressions of emotion regularly used by us is essential to gain insights into human cognition and affect as well as for the design of computational models and perceptual interfaces. Past research on facial expressions of emotion has focused on the study of six basic categories--happiness, surprise, anger, sadness, fear, and disgust. However, many more facial expressions of emotion exist and are used regularly by humans. This paper describes an important group of expressions, which we call compound emotion categories. Compound emotions are those that can be constructed by combining basic component categories to create new ones. For instance, happily surprised and angrily surprised are two distinct compound emotion categories. The present work defines 21 distinct emotion categories. Sample images of their facial expressions were collected from 230 human subjects. A Facial Action Coding System analysis shows the production of these 21 categories is different but consistent with the subordinate categories they represent (e.g., a happily surprised expression combines muscle movements observed in happiness and surprised). We show that these differences are sufficient to distinguish between the 21 defined categories. We then use a computational model of face perception to demonstrate that most of these categories are also visually discriminable from one another. Understanding the different categories of facial expressions of emotion regularly used by us is essential to gain insights into human cognition and affect as well as for the design of computational models and perceptual interfaces. Past research on facial expressions of emotion has focused on the study of six basic categories—happiness, surprise, anger, sadness, fear, and disgust. However, many more facial expressions of emotion exist and are used regularly by humans. This paper describes an important group of expressions, which we call compound emotion categories. Compound emotions are those that can be constructed by combining basic component categories to create new ones. For instance, happily surprised and angrily surprised are two distinct compound emotion categories. The present work defines 21 distinct emotion categories. Sample images of their facial expressions were collected from 230 human subjects. A Facial Action Coding System analysis shows the production of these 21 categories is different but consistent with the subordinate categories they represent (e.g., a happily surprised expression combines muscle movements observed in happiness and surprised). We show that these differences are sufficient to distinguish between the 21 defined categories. We then use a computational model of face perception to demonstrate that most of these categories are also visually discriminable from one another. |
| Author | Aleix M. Martinez Yong Tao Shichuan Du |
| Author_xml | – sequence: 1 givenname: Shichuan surname: Du fullname: Du, Shichuan organization: Department of Electrical and Computer Engineering, and Center for Cognitive and Brain Sciences, The Ohio State University, Columbus, OH 43210 – sequence: 2 givenname: Yong surname: Tao fullname: Tao, Yong organization: Department of Electrical and Computer Engineering, and Center for Cognitive and Brain Sciences, The Ohio State University, Columbus, OH 43210 – sequence: 3 givenname: Aleix M. surname: Martinez fullname: Martinez, Aleix M. organization: Department of Electrical and Computer Engineering, and Center for Cognitive and Brain Sciences, The Ohio State University, Columbus, OH 43210 |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24706770$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1037/0033-2909.115.1.102 10.1016/j.neuron.2013.10.038 10.1023/A:1015469627679 10.1016/j.psychres.2004.07.003 10.1167/9.1.5 10.1016/0042-6989(80)90065-6 10.1038/nrn2920 10.1109/CVPR.2010.5539998 10.1017/S0140525X11000446 10.1109/34.817413 10.1146/annurev.psych.60.110707.163539 10.1093/scan/nsq069 10.1109/TPAMI.2010.28 10.1016/j.patcog.2011.09.023 10.1016/0010-0277(92)90002-Y 10.1037/0033-295X.110.1.145 10.1109/TPAMI.2005.250 10.1016/S0042-6989(03)00079-8 10.1109/34.824823 10.1137/1.9781611970128 10.1198/016214504000000098 10.1080/02699939208411068 10.3758/BRM.42.1.351 10.1109/TPAMI.2002.1008382 10.1016/j.tics.2012.09.006 10.1016/j.jneumeth.2011.06.023 10.1109/JPROC.2006.884093 10.1109/ICCV.2009.5459365 10.1007/978-0-85729-997-0_19 10.7208/chicago/9780226220802.001.0001 10.1109/TPAMI.2005.90 10.1167/11.13.24 10.1109/TPAMI.2010.173 10.1016/j.patcog.2013.06.013 |
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| References | Ekman P (e_1_3_3_12_2) 1978 Martinez AM (e_1_3_3_5_2) 2012; 13 e_1_3_3_17_2 e_1_3_3_16_2 e_1_3_3_19_2 e_1_3_3_38_2 e_1_3_3_18_2 e_1_3_3_39_2 e_1_3_3_13_2 e_1_3_3_36_2 e_1_3_3_37_2 e_1_3_3_15_2 e_1_3_3_34_2 e_1_3_3_14_2 e_1_3_3_35_2 e_1_3_3_32_2 e_1_3_3_11_2 e_1_3_3_30_2 e_1_3_3_10_2 e_1_3_3_31_2 e_1_3_3_40_2 Borod JC (e_1_3_3_4_2) 2000 cr-split#-e_1_3_3_3_2.2 e_1_3_3_6_2 Ekman P (e_1_3_3_7_2) 1976 e_1_3_3_8_2 e_1_3_3_28_2 e_1_3_3_9_2 e_1_3_3_27_2 cr-split#-e_1_3_3_3_2.1 e_1_3_3_29_2 e_1_3_3_24_2 e_1_3_3_23_2 e_1_3_3_26_2 Vapnik V (e_1_3_3_44_2) 1999 e_1_3_3_45_2 e_1_3_3_25_2 e_1_3_3_2_2 e_1_3_3_20_2 e_1_3_3_43_2 e_1_3_3_1_2 e_1_3_3_22_2 e_1_3_3_41_2 e_1_3_3_21_2 Fisher RA (e_1_3_3_33_2) 1938; 8 e_1_3_3_42_2 7467139 - Vision Res. 1980;20(10):847-56 22617651 - Behav Brain Sci. 2012 Jun;35(3):121-43 12676247 - Vision Res. 2003 Apr;43(9):1047-60 16358412 - IEEE Trans Pattern Anal Mach Intell. 2005 Dec;27(12):1934-44 19271875 - J Vis. 2009;9(1):5.1-11 20160315 - Behav Res Methods. 2010 Feb;42(1):351-62 23950695 - J Mach Learn Res. 2012 May 1;13:1589-1608 20959860 - Nat Rev Neurosci. 2010 Nov;11(11):773-83 20847391 - IEEE Trans Pattern Anal Mach Intell. 2010 Nov;32(11):2022-38 8202574 - Psychol Bull. 1994 Jan;115(1):102-41 18729725 - Annu Rev Psychol. 2009;60:1-25 20820072 - IEEE Trans Pattern Anal Mach Intell. 2011 Mar;33(3):631-8 24187386 - Pattern Recognit. 2014 Jan 1;47(1):null 12529060 - Psychol Rev. 2003 Jan;110(1):145-72 22308002 - Pattern Recognit. 2012 Apr;45(4):1792-1801 15875802 - IEEE Trans Pattern Anal Mach Intell. 2005 May;27(5):812-6 22131445 - J Vis. 2011;11(13):24 23047070 - Trends Cogn Sci. 2012 Nov;16(11):559-72 15541780 - Psychiatry Res. 2004 Oct 30;128(3):235-44 20650943 - Soc Cogn Affect Neurosci. 2011 Apr;6(2):186-94 24183030 - Neuron. 2013 Oct 30;80(3):816-26 1424493 - Cognition. 1992 Sep;44(3):227-40 21741407 - J Neurosci Methods. 2011 Sep 15;200(2):237-56 |
| References_xml | – ident: e_1_3_3_2_2 doi: 10.1037/0033-2909.115.1.102 – ident: e_1_3_3_40_2 doi: 10.1016/j.neuron.2013.10.038 – volume-title: Pictures of Facial Affect year: 1976 ident: e_1_3_3_7_2 – ident: e_1_3_3_45_2 doi: 10.1023/A:1015469627679 – ident: e_1_3_3_13_2 doi: 10.1016/j.psychres.2004.07.003 – ident: e_1_3_3_28_2 doi: 10.1167/9.1.5 – ident: e_1_3_3_30_2 doi: 10.1016/0042-6989(80)90065-6 – ident: #cr-split#-e_1_3_3_3_2.2 – ident: e_1_3_3_1_2 – volume-title: The Nature of Statistical Learning Theory year: 1999 ident: e_1_3_3_44_2 – ident: e_1_3_3_29_2 doi: 10.1038/nrn2920 – ident: e_1_3_3_25_2 doi: 10.1109/CVPR.2010.5539998 – ident: e_1_3_3_11_2 doi: 10.1017/S0140525X11000446 – volume: 8 start-page: 376 year: 1938 ident: e_1_3_3_33_2 article-title: The statistical utilization of multiple measurements publication-title: Ann Hum Genet – ident: e_1_3_3_17_2 – ident: e_1_3_3_31_2 doi: 10.1109/34.817413 – ident: e_1_3_3_9_2 doi: 10.1146/annurev.psych.60.110707.163539 – ident: e_1_3_3_15_2 doi: 10.1093/scan/nsq069 – ident: e_1_3_3_18_2 doi: 10.1109/TPAMI.2010.28 – volume: 13 start-page: 1589 year: 2012 ident: e_1_3_3_5_2 article-title: A model of the perception of facial expressions of emotion by humans: Research overview and perspectives publication-title: J Mach Learn Res – ident: e_1_3_3_22_2 doi: 10.1016/j.patcog.2011.09.023 – ident: e_1_3_3_27_2 doi: 10.1016/0010-0277(92)90002-Y – ident: e_1_3_3_8_2 doi: 10.1037/0033-295X.110.1.145 – ident: e_1_3_3_32_2 doi: 10.1109/TPAMI.2005.250 – ident: e_1_3_3_26_2 doi: 10.1016/S0042-6989(03)00079-8 – ident: e_1_3_3_42_2 doi: 10.1109/34.824823 – ident: #cr-split#-e_1_3_3_3_2.1 – ident: e_1_3_3_35_2 doi: 10.1137/1.9781611970128 – ident: e_1_3_3_36_2 doi: 10.1198/016214504000000098 – ident: e_1_3_3_10_2 doi: 10.1080/02699939208411068 – ident: e_1_3_3_43_2 doi: 10.3758/BRM.42.1.351 – ident: e_1_3_3_38_2 doi: 10.1109/TPAMI.2002.1008382 – ident: e_1_3_3_41_2 doi: 10.1016/j.tics.2012.09.006 – volume-title: Facial Action Coding System: A Technique for the Measurement of Facial Movement year: 1978 ident: e_1_3_3_12_2 – ident: e_1_3_3_14_2 doi: 10.1016/j.jneumeth.2011.06.023 – ident: e_1_3_3_20_2 doi: 10.1109/JPROC.2006.884093 – ident: e_1_3_3_21_2 doi: 10.1109/ICCV.2009.5459365 – ident: e_1_3_3_23_2 doi: 10.1007/978-0-85729-997-0_19 – volume-title: The Neuropsychology of Emotion year: 2000 ident: e_1_3_3_4_2 – ident: e_1_3_3_24_2 – ident: e_1_3_3_6_2 doi: 10.7208/chicago/9780226220802.001.0001 – ident: e_1_3_3_39_2 doi: 10.1109/TPAMI.2005.90 – ident: e_1_3_3_37_2 doi: 10.1167/11.13.24 – ident: e_1_3_3_34_2 doi: 10.1109/TPAMI.2010.173 – ident: e_1_3_3_16_2 – ident: e_1_3_3_19_2 doi: 10.1016/j.patcog.2013.06.013 – reference: 24187386 - Pattern Recognit. 2014 Jan 1;47(1):null – reference: 1424493 - Cognition. 1992 Sep;44(3):227-40 – reference: 8202574 - Psychol Bull. 1994 Jan;115(1):102-41 – reference: 20160315 - Behav Res Methods. 2010 Feb;42(1):351-62 – reference: 23047070 - Trends Cogn Sci. 2012 Nov;16(11):559-72 – reference: 7467139 - Vision Res. 1980;20(10):847-56 – reference: 12529060 - Psychol Rev. 2003 Jan;110(1):145-72 – reference: 21741407 - J Neurosci Methods. 2011 Sep 15;200(2):237-56 – reference: 19271875 - J Vis. 2009;9(1):5.1-11 – reference: 20959860 - Nat Rev Neurosci. 2010 Nov;11(11):773-83 – reference: 22308002 - Pattern Recognit. 2012 Apr;45(4):1792-1801 – reference: 24183030 - Neuron. 2013 Oct 30;80(3):816-26 – reference: 23950695 - J Mach Learn Res. 2012 May 1;13:1589-1608 – reference: 20847391 - IEEE Trans Pattern Anal Mach Intell. 2010 Nov;32(11):2022-38 – reference: 15541780 - Psychiatry Res. 2004 Oct 30;128(3):235-44 – reference: 16358412 - IEEE Trans Pattern Anal Mach Intell. 2005 Dec;27(12):1934-44 – reference: 20650943 - Soc Cogn Affect Neurosci. 2011 Apr;6(2):186-94 – reference: 12676247 - Vision Res. 2003 Apr;43(9):1047-60 – reference: 22131445 - J Vis. 2011;11(13):24 – reference: 22617651 - Behav Brain Sci. 2012 Jun;35(3):121-43 – reference: 20820072 - IEEE Trans Pattern Anal Mach Intell. 2011 Mar;33(3):631-8 – reference: 15875802 - IEEE Trans Pattern Anal Mach Intell. 2005 May;27(5):812-6 – reference: 18729725 - Annu Rev Psychol. 2009;60:1-25 |
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| Title | Compound facial expressions of emotion |
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