en
Proceedings chapter
English

RankTrace: Relative and unbounded affect annotation

Presented at San Antonio (TX), 23-26 Oct. 2017
PublisherIEEE
Publication date2017
Abstract

How should annotation data be processed so that it can best characterize the ground truth of affect? This paper attempts to address this critical question by testing various methods of processing annotation data on their ability to capture phasic elements of skin conductance. Towards this goal the paper introduces a new affect annotation tool, RankTrace, that allows for the annotation of affect in a continuous yet unbounded fashion. RankTrace is tested on first-person annotations of tension elicited from a horror video game. The key findings of the paper suggest that the relative processing of traces via their mean gradient yields the best and most robust predictors of phasic manifestations of skin conductance.

Keywords
  • Affective computing
  • Computer games
  • Emotion recognition
  • Medical signal processing
Citation (ISO format)
LOPES, Phil, YANNAKAKIS, Georgios N., LIAPIS, Antonios. RankTrace: Relative and unbounded affect annotation. In: Seventh International Conference on Affective Computing and Intelligent Interaction (ACII 2017). San Antonio (TX). [s.l.] : IEEE, 2017. p. 158–163. doi: 10.1109/ACII.2017.8273594
Main files (1)
Proceedings chapter (Published version)
accessLevelRestricted
Identifiers
ISBN978-1-5386-0563-9
106views
0downloads

Technical informations

Creation06/03/2021 5:08:00 PM
First validation06/03/2021 5:08:00 PM
Update time03/16/2023 12:42:27 AM
Status update03/16/2023 12:42:26 AM
Last indexation01/17/2024 1:25:21 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack