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ChaLearn LAP 2016: First Round Challenge on First Impressions - Dataset and Results
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Title:
ChaLearn LAP 2016: First Round Challenge on First Impressions - Dataset and Results
Author:
Ponce-Lopez, V
;
Chen, B
;
Oliu, M
;
Corneanu, C
;
Clapes, A
;
Guyon, I
;
Baro, X
;
Escalante, HJ
;
Escalera, S
Subjects:
Artificial Intelligence
;
BEHAVIOR
;
Behavior analysis
;
Computer Science
;
First impressions
;
Information Systems
;
PERSONALITY
;
Personality traits
;
Science & Technology
;
Technology
;
Theory & Methods
;
THIN SLICES
;
VALIDITY
Description:
This paper summarizes the ChaLearn Looking at People 2016 First Impressions challenge data and results obtained by the teams in the first round of the competition. The goal of the competition was to automatically evaluate five “apparent” personality traits (the so-called “Big Five”) from videos of subjects speaking in front of a camera, by using human judgment. In this edition of the ChaLearn challenge, a novel data set consisting of 10,000 shorts clips from YouTube videos has been made publicly available. The ground truth for personality traits was obtained from workers of Amazon Mechanical Turk (AMT). To alleviate calibration problems between workers, we used pairwise comparisons between videos, and variable levels were reconstructed by fitting a Bradley-Terry-Luce model with maximum likelihood. The CodaLab open source platform was used for submission of predictions and scoring. The competition attracted, over a period of 2 months, 84 participants who are grouped in several teams. Nine teams entered the final phase. Despite the difficulty of the task, the teams made great advances in this round of the challenge.
Publisher:
Springer
Creation Date:
2016
Language:
English
Source:
UCL Discovery
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