TY  - CONF
AU  - Julio C. S. Jacques Junior
AU  - Agata Lapedriza
AU  - Cristina Palmero
AU  - Xavier Baro
AU  - Sergio Escalera
A2  - WACV
PY  - 2021//
TI  - Person Perception Biases Exposed: Revisiting the First Impressions Dataset
BT  - IEEE Winter Conference on Applications of Computer Vision
SP  - 13
EP  - 21
N2  - This work revisits the ChaLearn First Impressions database, annotated for personality perception using pairwise comparisons via crowdsourcing. We analyse for the first time the original pairwise annotations, and reveal existing person perception biases associated to perceived attributes like gender, ethnicity, age and face attractiveness.We show how person perception bias can influence data labelling of a subjective task, which has received little attention from the computer vision and machine learning communities by now. We further show that the mechanism used to convert pairwise annotations to continuous values may magnify the biases if no special treatment is considered. The findings of this study are relevant for the computer vision community that is still creating new datasets on subjective tasks, and using them for practical applications, ignoring these perceptual biases.
L1  - http://refbase.cvc.uab.es/files/JLP2021.pdf
UR  - http://dx.doi.org/10.1109/WACVW52041.2021.00006
N1  - HUPBA
ID  - Julio C. S. Jacques Junior2021
ER  -