Personality Perception in Human Videos Altered by Motion Transfer Networks
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866916106376052736 |
|---|---|
| author | Yurtoğlu, Ayda Sonlu, Sinan Doğan, Yalım Güdükbay, Uğur |
| author_facet | Yurtoğlu, Ayda Sonlu, Sinan Doğan, Yalım Güdükbay, Uğur |
| contents | The successful portrayal of personality in digital characters improves communication and immersion. Current research focuses on expressing personality through modifying animations using heuristic rules or data-driven models. While studies suggest motion style highly influences the apparent personality, the role of appearance can be similarly essential. This work analyzes the influence of movement and appearance on the perceived personality of short videos altered by motion transfer networks. We label the personalities in conference video clips with a user study to determine the samples that best represent the Five-Factor model's high, neutral, and low traits. We alter these videos using the Thin-Plate Spline Motion Model, utilizing the selected samples as the source and driving inputs. We follow five different cases to study the influence of motion and appearance on personality perception. Our comparative study reveals that motion and appearance influence different factors: motion strongly affects perceived extraversion, and appearance helps convey agreeableness and neuroticism. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_14733 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Personality Perception in Human Videos Altered by Motion Transfer Networks Yurtoğlu, Ayda Sonlu, Sinan Doğan, Yalım Güdükbay, Uğur Computer Vision and Pattern Recognition 65D18 (Primary), 91E30 (Secondary) The successful portrayal of personality in digital characters improves communication and immersion. Current research focuses on expressing personality through modifying animations using heuristic rules or data-driven models. While studies suggest motion style highly influences the apparent personality, the role of appearance can be similarly essential. This work analyzes the influence of movement and appearance on the perceived personality of short videos altered by motion transfer networks. We label the personalities in conference video clips with a user study to determine the samples that best represent the Five-Factor model's high, neutral, and low traits. We alter these videos using the Thin-Plate Spline Motion Model, utilizing the selected samples as the source and driving inputs. We follow five different cases to study the influence of motion and appearance on personality perception. Our comparative study reveals that motion and appearance influence different factors: motion strongly affects perceived extraversion, and appearance helps convey agreeableness and neuroticism. |
| title | Personality Perception in Human Videos Altered by Motion Transfer Networks |
| topic | Computer Vision and Pattern Recognition 65D18 (Primary), 91E30 (Secondary) |
| url | https://arxiv.org/abs/2401.14733 |