Paper Info
Title
Eye Tracking for Target Acquisition in Sparse Visualizations
Abstract
In this paper, we present a novel marker-free method for identifying screens of interest when using head-mounted eye tracking for visualization in cluttered and multi-screen environments. We offer a solution to discerning visualization entities from sparse backgrounds by incorporating edge-detection into the existing pipeline. Our system allows for both more efficient screen identification and improved accuracy over the state-of-the-art ORB algorithm.
Year
DOI
Venue
2020
10.1145/3379156.3391834
ETRA '20: 2020 Symposium on Eye Tracking Research and Applications Stuttgart Germany June, 2020
Keywords
DocType
ISBN
HCI, computer vision, gaze detection, Multi-user
Conference
978-1-4503-7134-6
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Sir Feiyang Wang100.34
Adam James Bradley252.43
Christopher Collins3103749.74