Eye Movement Feature Classification for Soccer Goalkeeper Expertise Identification in Virtual Reality
September 23, 2020 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Benedikt Hosp, Florian Schultz, Oliver HΓΆner, Enkelejda Kasneci
arXiv ID
2009.11676
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI,
cs.CV,
cs.LG
Citations
4
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The latest research in expertise assessment of soccer players has affirmed the importance of perceptual skills (especially for decision making) by focusing either on high experimental control or on a realistic presentation. To assess the perceptual skills of athletes in an optimized manner, we captured omnidirectional in-field scenes and showed these to 12 expert, 10 intermediate and 13 novice soccer goalkeepers on virtual reality glasses. All scenes were shown from the same natural goalkeeper perspective and ended after the return pass to the goalkeeper. Based on their gaze behavior we classified their expertise with common machine learning techniques. This pilot study shows promising results for objective classification of goalkeepers expertise based on their gaze behaviour and provided valuable insight to inform the design of training systems to enhance perceptual skills of athletes.
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