Title
Ferns for area of interest free scanpath classification
Abstract
Scanpath classification can offer insight into the visual strategies of groups such as experts and novices. We propose to use random ferns in combination with saccade angle successions to compare scanpaths. One advantage of our method is that it does not require areas of interest to be computed or annotated. The conditional distribution in random ferns additionally allows for learning angle successions, which do not have to be entirely present in a scanpath. We evaluated our approach on two publicly available datasets and improved the classification accuracy by ≈ 10 and ≈ 20 percent.
Year
DOI
Venue
2019
10.1145/3314111.3319826
Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications
Keywords
Field
DocType
eye tracking, random ferns, scanpath analysis
Psychology,Area of interest,Cartography
Conference
ISBN
Citations 
PageRank 
978-1-4503-6709-7
1
0.35
References 
Authors
0
6
Name
Order
Citations
PageRank
wolfgang fuhl112311.95
Nora Castner231.05
Thomas C. Kübler312412.57
Alexander Lotz410.35
Wolfgang Rosenstiel51462212.32
Enkelejda Kasneci620233.86