The more the merrier: Analysing the affect of a group of people in images

Abhinav DHALL, Jyoti Joshi, Karan Sikka, Roland GOECKE, Nicu Sebe

Research output: A Conference proceeding or a Chapter in BookConference contribution

41 Citations (Scopus)

Abstract

The recent advancement of social media has given users a platform to socially engage and interact with a global population. With millions of images being uploaded onto social media platforms, there is an increasing interest in inferring the emotion and mood display of a group of people in images. Automatic affect analysis research has come a long way but has traditionally focussed on a single subject in a scene. In this paper, we study the problem of inferring the emotion of a group of people in an image. This group affect has wide applications in retrieval, advertisement, content recommendation and security. The contributions of the paper are: 1) a novel emotion labelled database of groups of people in images; 2) a Multiple Kernel Learning based hybrid affect inference model; 3) a scene context based affect inference model; 4) a user survey to better understand the attributes that affect the perception of affect of a group of people in an image. The detailed experimentation validation provides a rich baseline for the proposed database.
Original languageEnglish
Title of host publication11th IEE International conference and workshop on Automatic face and gesture recognition (FG 2015)
EditorsKevin Bowyer, Ales Leonardis, Jeff Cohn
Place of PublicationSlovenia
PublisherIEEE
Pages1-8
Number of pages8
Volume1
ISBN (Electronic)9781479960262
ISBN (Print)9781479960262
DOIs
Publication statusPublished - 4 May 2015
Event11th IEEE International conference and workshop on Automatic face and gesture recognition 2015 - Ljubljana, Ljubljana, Slovenia
Duration: 4 May 20158 May 2015
http://www.fg2015.org/ (Conference website)

Publication series

Name2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015

Conference

Conference11th IEEE International conference and workshop on Automatic face and gesture recognition 2015
CountrySlovenia
CityLjubljana
Period4/05/158/05/15
OtherThe IEEE conference series on Automatic Face and Gesture Recognition is the premier international forum for research in image and video-based face, gesture, and body movement recognition. Its broad scope includes: advances in fundamental computer vision, pattern recognition and computer graphics; machine learning techniques relevant to face, gesture, and body motion; new algorithms and applications. The conference presents research that advances the state-of-the-art in these and related areas, leading to new capabilities in various application domains
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DHALL, A., Joshi, J., Sikka, K., GOECKE, R., & Sebe, N. (2015). The more the merrier: Analysing the affect of a group of people in images. In K. Bowyer, A. Leonardis, & J. Cohn (Eds.), 11th IEE International conference and workshop on Automatic face and gesture recognition (FG 2015) (Vol. 1, pp. 1-8). [7163151] (2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015). Slovenia: IEEE. https://doi.org/10.1109/FG.2015.7163151
DHALL, Abhinav ; Joshi, Jyoti ; Sikka, Karan ; GOECKE, Roland ; Sebe, Nicu. / The more the merrier: Analysing the affect of a group of people in images. 11th IEE International conference and workshop on Automatic face and gesture recognition (FG 2015). editor / Kevin Bowyer ; Ales Leonardis ; Jeff Cohn. Vol. 1 Slovenia : IEEE, 2015. pp. 1-8 (2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015).
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abstract = "The recent advancement of social media has given users a platform to socially engage and interact with a global population. With millions of images being uploaded onto social media platforms, there is an increasing interest in inferring the emotion and mood display of a group of people in images. Automatic affect analysis research has come a long way but has traditionally focussed on a single subject in a scene. In this paper, we study the problem of inferring the emotion of a group of people in an image. This group affect has wide applications in retrieval, advertisement, content recommendation and security. The contributions of the paper are: 1) a novel emotion labelled database of groups of people in images; 2) a Multiple Kernel Learning based hybrid affect inference model; 3) a scene context based affect inference model; 4) a user survey to better understand the attributes that affect the perception of affect of a group of people in an image. The detailed experimentation validation provides a rich baseline for the proposed database.",
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DHALL, A, Joshi, J, Sikka, K, GOECKE, R & Sebe, N 2015, The more the merrier: Analysing the affect of a group of people in images. in K Bowyer, A Leonardis & J Cohn (eds), 11th IEE International conference and workshop on Automatic face and gesture recognition (FG 2015). vol. 1, 7163151, 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015, IEEE, Slovenia, pp. 1-8, 11th IEEE International conference and workshop on Automatic face and gesture recognition 2015, Ljubljana, Slovenia, 4/05/15. https://doi.org/10.1109/FG.2015.7163151

The more the merrier: Analysing the affect of a group of people in images. / DHALL, Abhinav; Joshi, Jyoti; Sikka, Karan; GOECKE, Roland; Sebe, Nicu.

11th IEE International conference and workshop on Automatic face and gesture recognition (FG 2015). ed. / Kevin Bowyer; Ales Leonardis; Jeff Cohn. Vol. 1 Slovenia : IEEE, 2015. p. 1-8 7163151 (2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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T1 - The more the merrier: Analysing the affect of a group of people in images

AU - DHALL, Abhinav

AU - Joshi, Jyoti

AU - Sikka, Karan

AU - GOECKE, Roland

AU - Sebe, Nicu

PY - 2015/5/4

Y1 - 2015/5/4

N2 - The recent advancement of social media has given users a platform to socially engage and interact with a global population. With millions of images being uploaded onto social media platforms, there is an increasing interest in inferring the emotion and mood display of a group of people in images. Automatic affect analysis research has come a long way but has traditionally focussed on a single subject in a scene. In this paper, we study the problem of inferring the emotion of a group of people in an image. This group affect has wide applications in retrieval, advertisement, content recommendation and security. The contributions of the paper are: 1) a novel emotion labelled database of groups of people in images; 2) a Multiple Kernel Learning based hybrid affect inference model; 3) a scene context based affect inference model; 4) a user survey to better understand the attributes that affect the perception of affect of a group of people in an image. The detailed experimentation validation provides a rich baseline for the proposed database.

AB - The recent advancement of social media has given users a platform to socially engage and interact with a global population. With millions of images being uploaded onto social media platforms, there is an increasing interest in inferring the emotion and mood display of a group of people in images. Automatic affect analysis research has come a long way but has traditionally focussed on a single subject in a scene. In this paper, we study the problem of inferring the emotion of a group of people in an image. This group affect has wide applications in retrieval, advertisement, content recommendation and security. The contributions of the paper are: 1) a novel emotion labelled database of groups of people in images; 2) a Multiple Kernel Learning based hybrid affect inference model; 3) a scene context based affect inference model; 4) a user survey to better understand the attributes that affect the perception of affect of a group of people in an image. The detailed experimentation validation provides a rich baseline for the proposed database.

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PB - IEEE

CY - Slovenia

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DHALL A, Joshi J, Sikka K, GOECKE R, Sebe N. The more the merrier: Analysing the affect of a group of people in images. In Bowyer K, Leonardis A, Cohn J, editors, 11th IEE International conference and workshop on Automatic face and gesture recognition (FG 2015). Vol. 1. Slovenia: IEEE. 2015. p. 1-8. 7163151. (2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015). https://doi.org/10.1109/FG.2015.7163151