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Deepti Pappusetty
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for the Degree of Doctor of Philosophy (Ph.D.)
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"Analysis of Eye Response to Video Quality and Structure"
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Thurs., Nov. 9
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3 p.m.
777 Glades Rd., EE 405
FAU Boca Raton Campus
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DEPARTMENT: Computer and Electrical Engineering and Computer Science
CHAIR OF THE CANDIDATE’S PH.D. COMMITTEE: Hari Kalva, Ph.D.
PH.D. SUPERVISORY COMMITTEE:
Ankur Agarwal, Ph.D.
Daniel Raviv , Ph.D.
Oge Marques, Ph.D.
Howard S. Hock, Ph.D.
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ABSTRACT OF DISSERTATION
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Real-time human eye recognition and tracking systems with human-computer interaction mechanism are being adopted to advance user experience in smart devices and consumer electronic systems. Eye tracking systems measure eye gaze and pupil response non-intrusively. This research presents an analysis of eye pupil and gazes response to video structure and content. The set of experiments for this study involved presenting different video content to subjects and measuring eye response with an eye tracker. Results show significant changes in a video and scene cuts lead to sharp constrictions. User response to videos can provide insights that can improve subjective quality assessment metrics. This research also presents an analysis of the pupil and gaze response to quality changes in videos. The results show pupil constrictions for noticeable changes in perceived quality. Gaze responses show higher fixations/saccades ratios with lower video quality showcasing more effort by users in discerning features. Using real-time eye tracking systems for video analysis and quality evaluation can open a new class of applications for consumer electronic systems.
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BIOGRAPHICAL SKETCH
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- Born in India
- B.S. 2008, Jawaharlal Nehru Technological University, India
- M.S. 2011, Florida Atlantic University, Boca Raton, Florida
- Ph.D. 2017, Florida Atlantic University, Boca Raton, Florida
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CONCERNING PERIOD OF PREPARATION & QUALIFYING EXAMINATION
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Time in Preparation: 2013 - 2017
Qualifying Examination Passed: Spring 2014
Published Papers:
Pappusetty, D., & Kalva H. (2018). Measuring Video Quality by Eye Response, In Human Vision & Electronic Imaging Conference (Under Review).
Pappusetty, D., Kalva H., & Hock H. S. (2017). Pupil Response to Quality and Content Transitions in Videos. IEEE Transactions on Consumer Electronics (Accepted).
Pappusetty, D., & Kalva H. (2017). Eye Response to Blockiness Artifacts in Video. In European Conference on Eye Movements (ECEM) (In Press).
Pappusetty, D., Chinta, V. V. R., & Kalva, H. (2017). Using pupillary response to assess video quality. In IEEE International Conference on Consumer Electronics (ICCE) (pp. 64–65). https://doi.org/10.1109/ICCE.2017.7889231
Pappusetty, D., & Kalva, H. (2016). Reducing Inattentional Blindness Using Subliminal Cueing in Visual Performance Tasks. Electronic Imaging, 2016(16), 1–5. https://doi.org/10.2352/ISSN.2470-1173.2016.16.HVEI-118 (Honorary Mention 2nd Best Student Paper Award).
Bhatt, J., Pappusetty, D., Kalva, H., & Naik, M. (2016). Image retargeting for wearable devices. In 2016 IEEE International Conference on Consumer Electronics (ICCE) (pp. 55–57). https://doi.org/10.1109/ICCE.2016.7430520 (Best Student Paper Award).
Elafoudi, G., Stankovic, V., Stankovic, L., Pappusetty, D., & Kalva, H. (2015). Evaluation of Signal Processing Methods for Attention Assessment in Visual Content Interaction. In New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops (pp. 580–588). Springer, Cham. https://doi.org/10.1007/978-3-319-23222-5_70
Pappusetty, D., & Kalva, H. (2014). Effect of Subliminal Cueing on In-attentional Blindness. In Proceedings of the 1st International Workshop on Perception Inspired Video Processing (pp. 39–40). New York, NY, USA: ACM. https://doi.org/10.1145/2662996.2666156
Pappusetty, D., & Kalva, H. (2017). Eye Response as Video Quality Metric (Manuscript under preparation).
Patent Applications & Copyrights:
Kalva, H., & Pappusetty, D., System and Method to Reduce In-attentional Blindness and Change Blindness. Provisional patent application file No. FAU 201416.
Kalva, H., Pappusetty, D., & Furht, B, Software for Automated Data Backup. Copyright registration No. TXu001913320.
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777 Glades Road, EE 308, Boca Raton, FL 33431-0991•
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