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Author: Sheldon Schiffer

Affiliation: Department of Computer Science, Occidental College, 1600 Campus Road, Los Angeles, U.S.A.

Keyword(s): Facial Emotion Corpora, Emotion AI, Neural Networks, Non-Player Characters, Autonomous Agents.

Abstract: Single-actor facial emotion video corpora for training NN animation controllers allows for a workflow where game designers and actors can use their character performance training to significantly contribute to the authorial process of animated character behaviour. These efforts result in the creation of scripted and structured video samples for a corpus. But what are the measurable techniques to determine if a corpus sample collection or NN design adequately simulates an actor’s character for creating autonomous emotion-derived animation? This study focuses on the expression velocity of the predictive data generated by a NN animation controller and compares it to the expression velocity recorded in the ground truth performance of the eliciting actor’s test data. We analyse four targeted emotion labels to determine their statistical resemblance based on our proposed workflow and NN design. Our results show that statistical resemblance can be used to evaluate the accuracy of corpora an d NN designs. (More)

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Paper citation in several formats:
Schiffer, S. (2023). Measuring Emotion Velocity for Resemblance in Neural Network Facial Animation Controllers and Their Emotion Corpora. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 240-248. DOI: 10.5220/0011676200003393

@conference{icaart23,
author={Sheldon Schiffer.},
title={Measuring Emotion Velocity for Resemblance in Neural Network Facial Animation Controllers and Their Emotion Corpora},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2023},
pages={240-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011676200003393},
isbn={978-989-758-623-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Measuring Emotion Velocity for Resemblance in Neural Network Facial Animation Controllers and Their Emotion Corpora
SN - 978-989-758-623-1
IS - 2184-433X
AU - Schiffer, S.
PY - 2023
SP - 240
EP - 248
DO - 10.5220/0011676200003393
PB - SciTePress