Automated capture and delivery of assistive task guidance with an eyewear computer: the GlaciAR system

Teesid Leelasawassuk, Dima Damen, Walterio Mayol-Cuevas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

3 Citations (Scopus)
346 Downloads (Pure)


In this paper we describe and evaluate an assistive mixed reality system that aims to augment users in tasks by combining automated and unsupervised information collection with minimally invasive video guides. The result is a fully self-contained system that we call GlaciAR (Glass-enabled Contextual Interactions for Augmented Reality). It operates by extracting contextual interactions from observing users performing actions. GlaciAR is able to i) automatically determine moments of relevance based on a head motion attention model, ii) automatically produce video guidance information, iii) trigger these guides based on an object detection method, iv) learn without supervision from observing multiple users and v) operate fully on-board a current eyewear computer (Google Glass). We describe the components of GlaciAR together with user evaluations on three tasks. We see this work as a first step toward scaling up the notoriously difficult authoring problem in guidance systems and an exploration of enhancing user natural abilities via minimally invasive visual cues.
Original languageEnglish
Title of host publicationAH'17: Proceedings of the 8th Augmented Human International Conference
PublisherAssociation for Computing Machinery (ACM)
Number of pages9
ISBN (Electronic)9781450348355
Publication statusPublished - 18 Mar 2017
EventACM 8th Augmented Human International Conference - Silicon Valley, United States
Duration: 16 Mar 201718 Mar 2017


ConferenceACM 8th Augmented Human International Conference
Country/TerritoryUnited States
CitySilicon Valley


  • Augmented Reality
  • Task Guidance
  • Eyewear computing
  • Assistive computing


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