AUTHORS
ABSTRACT
Full Text: Evaluation of Webcam-Based Eye Tracking for a Job Interview Training Platform: Preliminary Results
In job interviews, eye gaze towards the interviewer is an important
non-verbal behavior that is considered a trait for hirability of
a candidate. Several virtual job interview training platforms include eye
trackers to measure eye gaze to provide feedback on performance. Though
useful, these eye tracking devices are often pricey and not always accessible.
In this article, we explore several camera-based eye tracking methods
and implement a webcam-based eye tracking algorithm to determine its
suitability for potential integration in virtual job interview simulation
platforms. We further use the gaze predictions for interview relevant
regions of interest detection. Our study with 12 participants, 7 with eyeglasses
and 5 without, shows that during calibration, eyeglasses play no
significant role in the differences in mean calibration error. Results from
the ROI detection, however, show a limitation that it is important to
maintain the same head position and distance during multiple tasks after
calibration. Overall, webcam-based eye-tracking has potential, to be
integrated in virtual job interview training environments.
Tags: CIRVR