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IEEE VR2024Top-tier venue

ARpenSki: Augmenting Ski Training with Direct and Indirect Postural Visualization

Takashi Matsumoto, Erwin Wu, Chen-Chieh Liao, Hideki Koike

2024Year
11Citations

Abstract

Alpine skiing is a popular winter sport, and several systems have been proposed to enhance training and improve efficiency. However, many existing systems rely on simulation-based environments, which suffer from drawbacks such as a gap between real skiing and the lack of body ownership. To address these limitations, we present ARpenSki, a novel augmented reality (AR) ski training system that employs a see-through head mounted display (HMD) to deliver augmented visual training cues that may be applied on real slopes. The proposed AR system provides a transparent view of the lower half of the field of vision, where we implemented three different AR-based direct and indirect postural visualization methods. We conducted an user study to investigate the influence of different visual cues in the AR environment. Our results indicate that a simple AR visualization of the user’s spine (Figure 1.2) yields the most favorable training performance, surpassing conventional visualizations by 7% improvement in the user’s posture. Building upon these promising findings, we further tested our system on real slopes and showed the potential of a real AR skiing application.

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