Slackliner 2.0: Real-time Training Assistance Through Life-size Feedback

Christian Murlowski; Florian Daiber; Felix Kosmalla; Antonio Krüger

In: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. ACM International Conference on Human Factors in Computing Systems (CHI-2019), May 4-9, Glasgow, United Kingdom, Pages INT012:1-INT012:4, CHI EA '19, ISBN 978-1-4503-5971-9, ACM, 2019.


In this demo, we present Slackliner 2.0, an interactive slackline training assistant which features head and skeleton tracking, and real-time feedback through life-size projection. Like in other sports, proper training leads to a faster increase of skill and lessens the risk of injuries. We chose a set of exercises from slackline literature and implemented an interactive trainer which guides the user through the exercises giving feedback if the exercises were executed correctly. Based on lessons learned from our study and prior demonstrations we present a revised version of Slackliner that uses head tracking to better guide the user's attention and movements. Additionally a new visual indicator informs the trainee about her arm posture during the performance. This has been also included in an updated post-analysis view that provides the trainee with more detailed feedback about her performance. The present demo showcases an interactive sports training system that provides in-situ feedback while following a well-guided learning procedure.

Weitere Links

CHI2019___Demo___Slackliner.pdf (pdf, 2 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence