Literature DB >> 29606917

FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge.

Michel F Valstar1, Enrique Sánchez-Lozano1, Jeffrey F Cohn2,3, László A Jeni3, Jeffrey M Girard2, Zheng Zhang4, Lijun Yin4, Maja Pantic5,6.   

Abstract

The field of Automatic Facial Expression Analysis has grown rapidly in recent years. However, despite progress in new approaches as well as benchmarking efforts, most evaluations still focus on either posed expressions, near-frontal recordings, or both. This makes it hard to tell how existing expression recognition approaches perform under conditions where faces appear in a wide range of poses (or camera views), displaying ecologically valid expressions. The main obstacle for assessing this is the availability of suitable data, and the challenge proposed here addresses this limitation. The FG 2017 Facial Expression Recognition and Analysis challenge (FERA 2017) extends FERA 2015 to the estimation of Action Units occurrence and intensity under different camera views. In this paper we present the third challenge in automatic recognition of facial expressions, to be held in conjunction with the 12th IEEE conference on Face and Gesture Recognition, May 2017, in Washington, United States. Two sub-challenges are defined: the detection of AU occurrence, and the estimation of AU intensity. In this work we outline the evaluation protocol, the data used, and the results of a baseline method for both sub-challenges.

Entities:  

Year:  2017        PMID: 29606917      PMCID: PMC5876027          DOI: 10.1109/FG.2017.107

Source DB:  PubMed          Journal:  Proc Int Conf Autom Face Gesture Recognit        ISSN: 1541-5058


  8 in total

1.  Estimating smile intensity: A better way.

Authors:  Jeffrey M Girard; Jeffrey F Cohn; Fernando De la Torre
Journal:  Pattern Recognit Lett       Date:  2015-11-15       Impact factor: 3.756

Review 2.  A survey of affect recognition methods: audio, visual, and spontaneous expressions.

Authors:  Zhihong Zeng; Maja Pantic; Glenn I Roisman; Thomas S Huang
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2009-01       Impact factor: 6.226

3.  In the Pursuit of Effective Affective Computing: The Relationship Between Features and Registration.

Authors:  S W Chew; P Lucey; S Lucey; J Saragih; J F Cohn; I Matthews; S Sridharan
Journal:  IEEE Trans Syst Man Cybern B Cybern       Date:  2012-05-07

Review 4.  Intraclass correlations: uses in assessing rater reliability.

Authors:  P E Shrout; J L Fleiss
Journal:  Psychol Bull       Date:  1979-03       Impact factor: 17.737

5.  A Functional Regression Approach to Facial Landmark Tracking.

Authors:  Enrique Sanchez-Lozano; Georgios Tzimiropoulos; Brais Martinez; Fernando De la Torre; Michel Valstar
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2017-08-29       Impact factor: 6.226

6.  Automated Facial Action Coding System for dynamic analysis of facial expressions in neuropsychiatric disorders.

Authors:  Jihun Hamm; Christian G Kohler; Ruben C Gur; Ragini Verma
Journal:  J Neurosci Methods       Date:  2011-06-29       Impact factor: 2.390

Review 7.  Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications.

Authors:  Ciprian Adrian Corneanu; Marc Oliu Simon; Jeffrey F Cohn; Sergio Escalera Guerrero
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2016-01-07       Impact factor: 6.226

8.  Multi-PIE.

Authors:  Ralph Gross; Iain Matthews; Jeff Cohn; Takeo Kanade; Simon Baker
Journal:  Proc Int Conf Autom Face Gesture Recognit       Date:  2010-05-01
  8 in total
  7 in total

1.  Automated Affect Detection in Deep Brain Stimulation for Obsessive-Compulsive Disorder: A Pilot Study.

Authors:  Jeffrey F Cohn; Michael S Okun; Laszlo A Jeni; Itir Onal Ertugrul; David Borton; Donald Malone; Wayne K Goodman
Journal:  Proc ACM Int Conf Multimodal Interact       Date:  2018-10

2.  Human-Guided Modality Informativeness for Affective States.

Authors:  Torsten Wörtwein; Lisa B Sheeber; Nicholas Allen; Jeffrey F Cohn; Louis-Philippe Morency
Journal:  Proc ACM Int Conf Multimodal Interact       Date:  2021-10

3.  Human Observers and Automated Assessment of Dynamic Emotional Facial Expressions: KDEF-dyn Database Validation.

Authors:  Manuel G Calvo; Andrés Fernández-Martín; Guillermo Recio; Daniel Lundqvist
Journal:  Front Psychol       Date:  2018-10-26

4.  Quantifying dynamic facial expressions under naturalistic conditions.

Authors:  Jayson Jeganathan; Megan Campbell; Matthew Hyett; Gordon Parker; Michael Breakspear
Journal:  Elife       Date:  2022-08-31       Impact factor: 8.713

5.  Unmasking the Devil in the Details: What Works for Deep Facial Action Coding?

Authors:  Koichiro Niinuma; Laszlo A Jeni; Itir Onal Ertugrul; Jeffrey F Cohn
Journal:  BMVC       Date:  2019-09

6.  Computational Assessment of Facial Expression Production in ASD Children.

Authors:  Marco Leo; Pierluigi Carcagnì; Cosimo Distante; Paolo Spagnolo; Pier Luigi Mazzeo; Anna Chiara Rosato; Serena Petrocchi; Chiara Pellegrino; Annalisa Levante; Filomena De Lumè; Flavia Lecciso
Journal:  Sensors (Basel)       Date:  2018-11-16       Impact factor: 3.576

7.  Current state of science in machine learning methods for automatic infant pain evaluation using facial expression information: study protocol of a systematic review and meta-analysis.

Authors:  Dan Cheng; Dianbo Liu; Lisa Liang Philpotts; Dana P Turner; Timothy T Houle; Lucy Chen; Miaomiao Zhang; Jianjun Yang; Wei Zhang; Hao Deng
Journal:  BMJ Open       Date:  2019-12-11       Impact factor: 2.692

  7 in total

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