Estimating Perceived Comfort in Virtual Humans based on Spatial and Spectral Entropy

Greice Pinho Dal Molin; Victor Flávio de Andrade Araujo; Soraia Raupp Musse

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Paper

Estimating Perceived Comfort in Virtual Humans based on Spatial and Spectral Entropy

Topics: Document Imaging in Business; Entertainment Imaging Applications; Face and Expression Recognition; Features Extraction; Human and Computer Interaction; Image and Video Coding and Compression; Machine Learning Technologies for Vision; Visual Attention and Image Saliency

In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, 436-443, 2022

Authors: Greice Pinho Dal Molin ; Victor Flávio de Andrade Araujo and Soraia Raupp Musse

Affiliation: School of Technology, Graduate Program in Computer Science, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil

Keyword(s): Visual Perception, Virtual Humans, Comfort, Uncanny Valley.

Abstract: Nowadays, we are increasingly exposed to applications with conversational agents or virtual humans. In the psychology literature, the perception of human faces is a research area well studied. In past years, many works have investigated human perception concerning virtual humans. The sense of discomfort perceived in certain virtual characters, discussed in Uncanny Valley (UV) theory, can be a key factor in our perceptual and cognitive discrimination. Understanding how this process happens is essential to avoid it in the process of modeling virtual humans. This paper investigates the relationship between images features and the comfort that human beings can feel about the animated characters created using Computer Graphics (CG). We introduce the CCS (Computed Comfort Score) metric to estimate the probable comfort/discomfort value that a particular virtual human face can generate in the subjects. We used local spatial and spectral entropy to extract features and show their relevance to the subjects’ evaluation. A model using Support Vector Regression (SVR) is proposed to compute the CCS. The results indicated approximately an accuracy of 80% for the tested images when compared with the perceptual data. (More)

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Paper citation in several formats:

Molin, G.; Araujo, V. and Musse, S. (2022). Estimating Perceived Comfort in Virtual Humans based on Spatial and Spectral Entropy. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 436-443. DOI: 10.5220/0010831300003124

@conference{visapp22,
author={Greice Pinho Dal Molin. and Victor Flávio de Andrade Araujo. and Soraia Raupp Musse.},
title={Estimating Perceived Comfort in Virtual Humans based on Spatial and Spectral Entropy},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={436-443},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010831300003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Estimating Perceived Comfort in Virtual Humans based on Spatial and Spectral Entropy
SN - 978-989-758-555-5
IS - 2184-4321
AU - Molin, G.
AU - Araujo, V.
AU - Musse, S.
PY - 2022
SP - 436
EP - 443
DO - 10.5220/0010831300003124
PB - SciTePress