Date of Award

4-23-2019

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

First Advisor

Mariofanna Milanova

Abstract

The following dissertation proposes a gaze estimation and an emotion recognition system, as this system proposed is a face analysis package which not only contains face detection, but also eye tracking, emotion recognition, eye detection, as well as eye estimation. The system is comprised of a facial emotion recognition that can recognize the seven emotions including happiness, anger, sadness, neutral, surprise, disgust, and fear. This part of the system has an implemented Active Shape Model (ASM) tracker, as it is the emotion recognition part of the system, which through the webcam input can track 116 facial landmarks points to obtain face expression features. A classifier is instigated, the support Vector machine (SVM), in order to strengthen the proposed system and recognize the seven emotions. The proposed system has a second part, the eye gaze estimation, in which it is responsible for the formation of the head model as well as presenting the Pose from Orthography and Scaling with Iterations (POSIT) and the Active Shape Model (ASM) algorithms, of which these algorithms are responsible to estimate position and head tracking estimation. Performance rate is increased of the proposed system to a 93.2 maximum. The system does not require a specific webcam model and contains a simple hardware configuration since it depends primarily and only of the webcam of the PC, making this to be the software’s most essential advantage.

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