Output details
11 - Computer Science and Informatics
Lancaster University
Article title
Eye Movement Analysis for Activity Recognition Using Electrooculography
Type
D - Journal article
Title of journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
Article number
-
Volume number
33
Issue number
4
First page of article
741
ISSN of journal
0162-8828
Year of publication
2011
Number of additional authors
3
Additional information
<21> Introduces eye movement pattern analysis for activity recognition. This is work of great novelty, presenting a host of new features for eye movement signal analysis, and first to demonstrate that a machine can classify everyday activities (in this study: reading, writing, browsing, video-watching and copying) solely by analyzing how the user’s eyes move (without needing to analyse what the eyes look at). Results were first shown at Ubicomp ’09 (13% acceptance rate) and then expanded in IEEE PAMI (Thomson Reuters: IF 4.91).
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
38
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
