Recurrence quantification analysis reveals eye-movement behavior differences between experts and novices
Preethi Vaidyanathan, Jeff Pelz, Cecilia Alm, Pengcheng Shi, Anne Haake
Proceedings of the Symposium on Eye Tracking Research and Applications, 2014, pp. 303--306.
Abstract: Understanding and characterizing perceptual expertise is a major bottleneck in developing intelligent systems. In knowledge-rich domains such as dermatology, perceptual expertise influences the diagnostic inferences made based on the visual input. This study uses eye movement data from 12 dermatology experts and 12 undergraduate novices while they inspected 34 dermatological images. This work investigates the differences in global and local temporal fixation patterns between the two groups using recurrence quantification analysis (RQA). The RQA measures reveal significant differences in both global and local temporal patterns between the two groups. Results show that experts tended to refixate previously inspected areas less often than did novices, and their refixations were more widely separated in time. Experts were also less likely to follow extended scan paths repeatedly than were novices. These results suggest the potential value of RQA measures in characterizing perceptual expertise. We also discuss potential use of the RQA method in understanding the interactions between experts' visual and linguistic behavior.
Article URL: http://doi.acm.org/10.1145/2578153.2578207
BibTeX format:
@inproceedings{10.1145-2578153.2578207,
  author = {Preethi Vaidyanathan and Jeff Pelz and Cecilia Alm and Pengcheng Shi and Anne Haake},
  title = {Recurrence quantification analysis reveals eye-movement behavior differences between experts and novices},
  booktitle = {Proceedings of the Symposium on Eye Tracking Research and Applications},
  pages = {303--306},
  year = {2014},
}
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