English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  EyeContext: Recognition of High-level Contextual Cues from Human Visual Behaviour

Bulling, A., Weichel, C., & Gellersen, H. (2013). EyeContext: Recognition of High-level Contextual Cues from Human Visual Behaviour. In S. Bødker, S. Brewster, P. Baudisch, M. Beaudouin-Lafon, & W. E. Mackay (Eds.), CHI 2013 (pp. 305-308). New York, NY: ACM. doi:10.1145/2470654.2470697.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0018-4C91-2 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0024-A1D1-B
Genre: Conference Paper
Latex : {EyeContext}: {Recognition} of High-level Contextual Cues from Human Visual Behaviour

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Bulling, Andreas1, Author           
Weichel, Christian2, Author
Gellersen, Hans2, Author
Affiliations:
1Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society, ou_1116547              
2External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: Automatic annotation of life logging data is challenging. In this work we present EyeContext, a system to infer high-level contextual cues from human visual behaviour. We conduct a user study to record eye movements of four participants over a full day of their daily life, totalling 42.5 hours of eye movement data. Participants were asked to self-annotate four non-mutually exclusive cues: social (interacting with somebody vs. no interaction), cognitive (concentrated work vs. leisure), physical (physically active vs. not active), and spatial (inside vs. outside a building). We evaluate a proof-of-concept EyeContext system that combines encoding of eye movements into strings and a spectrum string kernel support vector machine (SVM) classifier. Using person-dependent training, we obtain a top performance of 85.3% precision (98.0% recall) for recognising social interactions. Our results demonstrate the large information content available in long-term human visual behaviour and opens up new venues for research on eye-based behavioural monitoring and life logging.

Details

show
hide
Language(s): eng - English
 Dates: 20132013-04
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: bulling13_chi
DOI: 10.1145/2470654.2470697
 Degree: -

Event

show
hide
Title: The 31st Annual CHI Conference on Human Factors in Computing Systems
Place of Event: Paris, France
Start-/End Date: 2013-04-27 - 2013-05-02

Legal Case

show

Project information

show

Source 1

show
hide
Title: CHI 2013
  Abbreviation : CHI 2013
  Subtitle : Changing Perspectives ; The 31st Annual CHI Conference on Human Factors in Computing Systems, Conference Proceedings
  Other : SIGCHI Conference on Human Factors in Computing Systems
Source Genre: Proceedings
 Creator(s):
Bødker, Susanne1, Editor
Brewster, Steven1, Editor
Baudisch, Patrick1, Editor
Beaudouin-Lafon, Michel1, Editor
Mackay, Wendy E.1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: New York, NY : ACM
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 305 - 308 Identifier: ISBN: 978-1-4503-1899-0