Proceedings chapter

RankTrace: Relative and unbounded affect annotation

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

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.

  • 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
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Proceedings chapter (Published version)

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