Role of group level affect to find the Most Influential Person in images

Shreya Ghosh, Abhinav Dhall

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch


Group affect analysis is an important cue for predicting various group traits. Generally, the estimation of the group affect, emotional responses, eye gaze and position of people in images are the important cues to identify an important person from a group of people. The main focus of this paper is to explore the importance of group affect in finding the representative of a group. We call that person the “Most Influential Person” (for the first impression) or “leader” of a group. In order to identify the main visual cues for “Most Influential Person”, we conducted a user survey. Based on the survey statistics, we annotate the “influential persons” in 1000 images of Group AFfect database (GAF 2.0) via LabelMe toolbox and propose the “GAF-personage database”. In order to identify “Most Influential Person”, we proposed a DNN based Multiple Instance Learning (Deep MIL) method which takes deep facial features as input. To leverage the deep facial features, we first predict the individual emotion probabilities via CapsNet and rank the detected faces on the basis of it. Then, we extract deep facial features of the top-3 faces via VGG-16 network. Our method performs better than maximum facial area and saliency-based importance methods and achieves the human-level perception of “Most Influential Person” at group-level.

Original languageEnglish
Title of host publicationComputer Vision – ECCV 2018 Workshops
Subtitle of host publicationMunich, Germany, September 8–14, 2018 Proceedings, Part II
EditorsLaura Leal-Taixé, Stefan Roth
Place of PublicationCham Switzerland
Number of pages16
ISBN (Electronic)9783030110123
ISBN (Print)9783030110116
Publication statusPublished - 2019
EventInternational workshop on human behavior understanding 2018 - Munich, Germany
Duration: 8 Sep 201814 Sep 2018
Conference number: 9th

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational workshop on human behavior understanding 2018
Internet address


  • Group level affect
  • Group of people
  • Important person

Cite this

Ghosh, S., & Dhall, A. (2019). Role of group level affect to find the Most Influential Person in images. In L. Leal-Taixé, & S. Roth (Eds.), Computer Vision – ECCV 2018 Workshops: Munich, Germany, September 8–14, 2018 Proceedings, Part II (pp. 518-533). (Lecture Notes in Computer Science ; Vol. 11130 ). Springer.