Automated data gathering and training tool for personalized "Itchy Nose"

Juyoung lee, Hui Shyong Yeo, Thad Starner, Aaron John Quigley, Kai Kunze, Woontack Woo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)
1 Downloads (Pure)

Abstract

In "Itchy Nose" we proposed a sensing technique for detecting finger movements on the nose for supporting subtle and discreet interaction. It uses the electrooculography sensors embedded in the frame of a pair of eyeglasses for data gathering and uses machine-learning technique to classify different gestures. Here we further propose an automated training and visualization tool for its classifier. This tool guides the user to make the gesture in proper timing and records the sensor data. It automatically picks the ground truth and trains a machine-learning classifier with it. With this tool, we can quickly create trained classifier that is personalized for the user and test various gestures.
Original languageEnglish
Title of host publicationAH '18 Proceedings of the 9th Augmented Human International Conference
Place of PublicationNew York
PublisherACM
Number of pages3
ISBN (Electronic)9781450354158
DOIs
Publication statusPublished - 7 Feb 2018
Event9th Augmented Human International Conference - Seoul, Korea, Democratic People's Republic of
Duration: 7 Feb 20189 Feb 2018
Conference number: 9
http://www.sigah.org/AH2018/

Conference

Conference9th Augmented Human International Conference
Abbreviated titleAH '18
Country/TerritoryKorea, Democratic People's Republic of
CitySeoul
Period7/02/189/02/18
Internet address

Keywords

  • Nose gesture
  • Subtle interaction
  • EOG
  • Wearable computer
  • Smart eyeglasses
  • Smart eyewear
  • Training tool
  • Online classification

Fingerprint

Dive into the research topics of 'Automated data gathering and training tool for personalized "Itchy Nose"'. Together they form a unique fingerprint.

Cite this