Capacitating surveillance and situational awareness with measure of visual engagement using eyetracker

Military application requires continuous surveillance and situation awareness at high security zones. For maintaining such requirements, there is a need to monitor visual attention for a defense personnel. Eye movements, captured through eye tracker can reveal visual engagements with the help of examining the direction of eye gaze. This not only reveals the opinion and behavioral patterns but also gives an idea that the brain can reveal hidden and profitable truths about consumers. Henceforth making it applicable in defense as well as in neuromarketing, as both domain want to grab visual attention of their personnel. This study tries to assess visual engagements through eye tracker using neuromarketing paradigm. Results can further be extended to the defense areas both fields involve visual attention. This paper investigates the use of Eyetracking as a potential research tool for analyzing the features that drives attention towards certain target (advertisement in this case). It is believed that eye movements are best indicators of visual attention. This paper gives an insight on the features that help us analyze visual attention and retention as tools to distinguish the effectiveness of the advertisement. The best feature of eye movements captured from eye tracking can identify glimpse of visual attention. Thus, making it greatly important in the use of defence as visual attention and henceforth brain reflexes are effected at immediate situations making it useful for surveillance, required feature in situational awareness and surveillance for border. This work here is of potential use in defence as it gives the measures of opinion and behavior of brain patterns of subjects revealing their hidden and profitable truths as that of customers.

[1]  Vidas Raudonis,et al.  Evaluation of Human Emotion from Eye Motions , 2013 .

[2]  Heiko Drewes,et al.  Eye gaze tracking for human computer interaction , 2010 .

[3]  Marcus Nyström,et al.  An adaptive algorithm for fixation, saccade, and glissade detection in eyetracking data , 2010, Behavior research methods.

[4]  Andrew T Duchowski,et al.  A breadth-first survey of eye-tracking applications , 2002, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[5]  E. Granholm,et al.  Pupillometric measures of cognitive and emotional processes. , 2004, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[6]  Joseph H. Goldberg,et al.  Identifying fixations and saccades in eye-tracking protocols , 2000, ETRA.

[7]  Manisha Satone,et al.  Selection of Eigenvectors for Face Recognition , 2013 .

[8]  Thomas W. Jackson,et al.  Emotion recognition — Theory or practicality , 2012, 18th International Conference on Automation and Computing (ICAC).

[9]  Jakob de Lemos,et al.  Measuring emotions using eye tracking , 2008 .

[10]  Samuel Kaski,et al.  Can Relevance be Inferred from Eye Movements in Information Retrieval , 2003 .

[11]  K. Rayner Eye movements in reading and information processing: 20 years of research. , 1998, Psychological bulletin.

[12]  Thorsten Joachims,et al.  Eye-tracking analysis of user behavior in WWW search , 2004, SIGIR '04.