Abstract
The aim of this study was to automatically identify the iris and pupil of the eye in the video stream and to parameterize the identified structures in order to make assumptions if the subjected is stressed or not. During tests subjects were given a number of issues which they had to respond by selecting only one correct answer. Visual material was gathered using a helmet-fitted stationary near-infrared camera that recorded iris and pupil of the eye reactions to stimuli. Subsequently it was made an automatic iris and pupil recognition and approximation by curves in the gathered sequence of images. Each change in the pupil size is described by different time series length. Thus, it is impossible to compare the obtained data using the Euclidean distance measures. For this reason, the metrics based on periodograms was used to compare the data series. The differences calculated between the eye pupil reaction to stimuli and question show-up time was introduced in multidimensional scaling algorithms for dimension reduction. It was noticed that the stimulus to the false answers tend to cluster. DOI: http://dx.doi.org/10.5755/j01.itc.41.1.1206
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
