Recognising emotions in human and synthetic faces

Costantini, Erica; Pianesi, Fabio; Prete, Michela Del

doi:10.1145/1040830.1040846

Cited by 16 publications

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our work, we exploit emotion transfer to evaluate the retargeting. Also Battocchi [27] and Costantini et al [28] used emotion judgment as mean of evaluation. However, as shown in [27], even if a professional actor perform the emotions, subjects falls into misinterpretation.…”

Section: Online Puppetry and Performance Capturementioning

confidence: 99%

Evaluation of a Facial Animation Authoring Pipeline Seamlessly Supporting Performance Capture and Manual Key-pose Editing

Nunnari¹,

Héloir²

2015

EAI Endorsed Transactions on Creative Technologies

View full text Add to dashboard Cite

In this paper, we present an architecture following a novel animation authoring pipeline seamlessly supporting performance capture and manual editing of key-frames animation. This pipeline allows novice users to record and author sophisticated facial animations in a fraction of the time that would be required using traditional animation tools. This approach paves the way towards novel animation pipelines which seamlessly merge the roles of the animator and the actor. The second contribution is a method assessing a facial retargeting system, we conducted a user study where participants assessed the emotions conveyed by the facial expression displayed in the control and the authored animation. Contrary to existing evaluation methods, it factors out possible misinterpretations of the intended emotion and focuses on assessing the retargeting quality.

show abstract

Section: Online Puppetry and Performance Capturementioning

confidence: 99%

Evaluation of a Facial Animation Authoring Pipeline Seamlessly Supporting Performance Capture and Manual Key-pose Editing

Nunnari¹,

Héloir²

2015

EAI Endorsed Transactions on Creative Technologies

View full text Add to dashboard Cite

show abstract

The Properties of DaFEx, a Database of Kinetic Facial Expressions

Battocchi¹,

Pianesi²,

Goren-Bar³

2005

Affective Computing and Intelligent Interaction

View full text Add to dashboard Cite

Perception of Blended Emotions: From Video Corpus to Expressive Agent

Buisine

Abrilian

Niewiadomski

et al. 2006

Intelligent Virtual Agents

View full text Add to dashboard Cite

Abstract. Real life emotions are often blended and involve several simultaneous superposed or masked emotions. This paper reports on a study on the perception of multimodal emotional behaviors in Embodied Conversational Agents. This experimental study aims at evaluating if people detect properly the signs of emotions in different modalities (speech, facial expressions, gestures) when they appear to be superposed or masked. We compared the perception of emotional behaviors annotated in a corpus of TV interviews and replayed by an expressive agent at different levels of abstraction. The results provide insights on the use of such protocols for studying the effect of various models and modalities on the perception of complex emotions.

show abstract

Recognising emotions in human and synthetic faces

Cited by 16 publications

References 6 publications

Evaluation of a Facial Animation Authoring Pipeline Seamlessly Supporting Performance Capture and Manual Key-pose Editing

Evaluation of a Facial Animation Authoring Pipeline Seamlessly Supporting Performance Capture and Manual Key-pose Editing

The Properties of DaFEx, a Database of Kinetic Facial Expressions

Perception of Blended Emotions: From Video Corpus to Expressive Agent

Contact Info

Product

Resources

About