Eye-2-I: Eye-tracking for just-in-time implicit user profiling

Eye-2-I: Eye-tracking for just-in-time implicit user profiling
Title:
Eye-2-I: Eye-tracking for just-in-time implicit user profiling
Other Titles:
IEEE International Conference on Signal and Image Processing (ICSIP)
DOI:
Publication Date:
11 August 2017
Citation:
Abstract:
For many applications, such as targeted advertising and content recommendation, knowing users' traits and interests is a prerequisite. User profiling is a helpful approach for this purpose. However, current methods, i.e. self-reporting, web-activity monitoring and social media mining are either intrusive or require data over long periods of time. Recently, there is growing evidence in cognitive science that a variety of users' profile is significantly correlated with eye-tracking data. A novel just-in-time implicit profiling method, Eye-2-I, which learns the user's demographic and personality traits from the eye-tracking data while the user is watching videos is proposed. Although seemingly conspicuous by closely monitoring the user's eye behaviors, the proposed method is unobtrusive and privacy-preserving owing to its unique combination of speed and implicitness. As a proof-of-concept, the proposed method is evaluated in a user study with 51 subjects.
License type:
PublisherCopyrights
Funding Info:
SeSaMe Centre at National University of Singapore; Reverse Engineering Visual Intelligence for cognitiVe Enhancement (REVIVE) programme funded by the Joint Council Office (JCO) of A*STAR (Grant No: 1335h00098)
Description:
(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISBN:

Files uploaded:

File Size Format Action
eye2i-final.pdf 667.86 KB PDF Open