EAT - The ICMI 2018 eating analysis and tracking challenge

Simone Hantke, Panagiotis Tzirakis, Maximilian Schmitt, Björn Schuller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

The multimodal recognition of eating condition - whether a person is eating or not - and if yes, which food type, is a new research domain in the area of speech and video processing that has many promising applications for future multimodal interfaces such as adapting speech recognition or lip reading systems to different eating conditions. We herein describe the ICMI 2018 Eating Analysis and Tracking (EAT) Challenge and address - for the first time in research competitions under well-defined conditions - new classification tasks in the area of user data analysis, namely audiovisual classifications of user eating conditions. We define three Sub-Challenges based on classification tasks in which participants are encouraged to use speech and/or video recordings of the audiovisual iHEARu-EAT database. In this paper, we describe the dataset, the Sub-Challenges, their conditions, and the baseline feature extraction and performance measures as provided to the participants.

Original languageEnglish
Title of host publicationICMI 2018 - Proceedings of the 2018 International Conference on Multimodal Interaction
PublisherAssociation for Computing Machinery, Inc
Pages559-563
Number of pages5
ISBN (Electronic)9781450356923
DOIs
StatePublished - 2 Oct 2018
Externally publishedYes
Event20th ACM International Conference on Multimodal Interaction, ICMI 2018 - Boulder, United States
Duration: 16 Oct 201820 Oct 2018

Publication series

NameICMI 2018 - Proceedings of the 2018 International Conference on Multimodal Interaction

Conference

Conference20th ACM International Conference on Multimodal Interaction, ICMI 2018
Country/TerritoryUnited States
CityBoulder
Period16/10/1820/10/18

Keywords

  • Challenge
  • Eating Condition
  • Human Behaviour
  • Multimodal Data Analysis

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