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Automatically Detecting Reading in Eye Tracking Data

To date, more and more eye tracking based studies are conducted to investigate reading under natural conditions (e.g. long texts, texts embedded with pictures etc.) and to investigate the perception of every day stimuli containing text (e.g. web pages, newspapers). When the data of such studies are to be statistically analyzed, it is often necessary to know when subjects are actually reading. Assuming that subjects are reading whenever they look at text is often a poor solution, because it would, for example, include scanning which is a very different process. In this paper, we depict a new, more elaborate but concise method to detect reading based on modeling fixationsaccade sequences with a Hidden Markov Model. The model can be used both off-line and on-line.