Name
Abstract | ||
|---|---|---|
In our society and century, clothing is not anymore used only as a means for body protection. Our paper builds upon the evidence, studied within the social sciences, that clothing brings a clear communicative message in terms of social signals, influencing the impression and behaviour of others towards a person. In fact, clothing correlates with personality traits, both in terms of self-assessment and assessments that unacquainted people give to an individual. The consequences of these facts are important: the influence of clothing on the decision making of individuals has been investigated in the literature, showing that it represents a discriminative factor to differentiate among diverse groups of people. Unfortunately, this has been observed after cumbersome and expensive manual annotations, on very restricted populations, limiting the scope of the resulting claims. With this position paper, we want to sketch the main steps of the very first systematic analysis, driven by social signal processing techniques, of the relationship between clothing and social signals, both sent and perceived. Thanks to human parsing technologies, which exhibit high robustness owing to deep learning architectures, we are now capable to isolate visual patterns characterising a large types of garments. These algorithms will be used to capture statistical relations on a large corpus of evidence to confirm the sociological findings and to go beyond the state of the art. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/FG.2017.71 | 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) |
Keywords | DocType | Volume |
social signal processing,communicative message,personality traits,unacquainted people,decision making,clothing,human parsing technologies,deep learning architectures,statistical relations | Conference | abs/1704.02231 |
ISSN | ISBN | Citations |
2326-5396 | 978-1-5090-4024-7 | 0 |
PageRank | References | Authors |
0.34 | 18 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maedeh Aghaei | 1 | 35 | 5.38 |
| Federico Parezzan | 2 | 0 | 0.34 |
| Mariella Dimiccoli | 3 | 89 | 18.29 |
| P. Radeva | 4 | 115 | 13.89 |
| M. Cristani | 5 | 1928 | 109.03 |