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A Hybrid Fuzzy Approach for Human Eye Gaze Pattern Recognition
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Document classification on relevance: a study on eye gaze patterns for reading
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Does the way a person read influence the way they understand information or is it the other way around? In regard to reading of English text, just how much we can learn from a person's gaze pattern? It is known that while reading, we inadvertently form rational connections between pieces of information we pick up from the text. That reflects in certain disruptions in the norms of reading paradigm and that gives us clues to our interest level in reading activities. In this paper, we validate the above statement and then propose a novel method of detecting the level of engagement in reading based on a person's gaze-pattern. We organised some experiments in reading tasks of over thirty participants and the experimental outputs are classified with Artificial Neural Networks with an approximately 80 percent accuracy. The design of this approach is simple and computationally feasible enough to be applied in a real-life system. "Your eyes are the windows to your soul"