I know what you are reading: recognition of document types using mobile eye tracking

Authors:
Kai Kunze;Yuzuko Utsumi;Yuki Shiga;Koichi Kise;Andreas Bulling
Affiliations:
Osaka Prefecture University, Sakai, Japan;Osaka Prefecture University, Sakai, Japan;Osaka Prefecture University, Sakai, Japan;Osaka Prefecture University, Sakai, Japan;Max Planck Institute for Informatics, Saarbrücken, Germany
Venue:
Proceedings of the 2013 International Symposium on Wearable Computers
Year:
2013

Citing 10
Cited 2

A survey of document image classification: problem statement, classifier architecture and performance evaluation

International Journal on Document Analysis and Recognition
An eye tracking study of how font size and type influence online reading

BCS-HCI '08 Proceedings of the 22nd British HCI Group Annual Conference on People and Computers: Culture, Creativity, Interaction - Volume 2
Eye Movement Analysis for Activity Recognition Using Electrooculography

IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of visual memory recall processes using eye movement analysis

Proceedings of the 13th international conference on Ubiquitous computing
Multimodal recognition of reading activity in transit using body-worn sensors

ACM Transactions on Applied Perception (TAP)
A robust realtime reading-skimming classifier

Proceedings of the Symposium on Eye Tracking Research and Applications
Towards robust gaze-based objective quality measures for text

Proceedings of the Symposium on Eye Tracking Research and Applications
Use of affine invariants in locally likely arrangement hashing for camera-based document image retrieval

DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Automatic text detection and tracking in digital video

IEEE Transactions on Image Processing
Towards inferring language expertise using eye tracking

CHI '13 Extended Abstracts on Human Factors in Computing Systems

My reading life: towards utilizing eyetracking on unmodified tablets and phones

Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Tracking how we read: activity recognition for cognitive tasks

XRDS: Crossroads, The ACM Magazine for Students - Wearable Computing: Getting Dressed in Tech

Quantified Score

Hi-index	0.00

Visualization

Abstract

Reading is a ubiquitous activity that many people even perform in transit, such as while on the bus or while walking. Tracking reading enables us to gain more insights about expertise level and potential knowledge of users -- towards a reading log tracking and improve knowledge acquisition. As a first step towards this vision, in this work we investigate whether different document types can be automatically detected from visual behaviour recorded using a mobile eye tracker. We present an initial recognition approach that com- bines special purpose eye movement features as well as machine learning for document type detection. We evaluate our approach in a user study with eight participants and five Japanese document types and achieve a recognition performance of 74% using user-independent training.