D. D. Salvucci. Inferring intent in eye-based interfaces: Tracing eye movements with process models. In Proceedings of the SIGCHI conference on Human factors in computing systems, pages 254–261, Pittsburgh, Pennsylvania, USA, May 15-20 1999. Association for Computing Machinery. [pdf]
While current eye-based interfaces offer enormous potential for efficient human-computer interaction, they also manifest the difficulty of inferring intent from user eye movements. This paper describes how fixation tracing facilitates the interpretation of eye movements and improves the flexibility and usability of eye-based interfaces. Fixation tracing uses hidden Markov models to map user actions to the sequential predictions of a cognitive process model. In a study of eye typing, results show that fixation tracing generates significantly more accurate interpretations than simpler methods and allows for more flexibility in designing usable interfaces. Implications for future research in eye-based interfaces and multimodal interfaces are discussed.
The main argument of this paper is that fixation tracing facilitates the analysis of eye movements to the user intentions that produced them. Tracing is the process of inferring intent by mapping observed actions to the sequential predictions of a process model. Fixation tracing interprets protocols by means of hidden Markov models, probabilistic models that have been used estensively in handwriting recognition.
Fixation tracing, according to the author, can interpret eye-movement protocols as accurately as human experts and can help in the creation, evaluation and refinement of cognitive models.
The author concludes saying that greater potential arises in the integration of eye movements with other input modelities as for instance, an interface in shich eye movements provide pointer or cursor positioning while speech allows typing or directed commands.