A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
HMM Based On-Line Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A gaze-based study for investigating the perception of visual realism in simulated scenes
ACM Transactions on Applied Perception (TAP)
Automated eye-movement protocol analysis
Human-Computer Interaction
Eye movement analysis for activity recognition
Proceedings of the 11th international conference on Ubiquitous computing
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It has been known for a long time that visual task, such as reading, counting and searching, greatly influences eye movement patterns. Perhaps the best known demonstration of this is the celebrated study of Yarbus showing that different eye movement trajectories emerge depending on the visual task that the viewers are given. The objective of this paper is to develop an inverse Yarbus process whereby we can infer the visual task by observing the measurements of a viewer's eye movements while executing the visual task. The method we are proposing is to use Hidden Markov Models (HMMs) to create a probabilistic framework to infer the viewer's task from eye movements.