ShuttleSpace: Exploring and Analyzing Movement Trajectory in Immersive Visualization

Abstract

We present ShuttleSpace, an immersive analytics system to assist experts in analyzing trajectory data in badminton. Trajectories in sports, such as the movement of players and balls, contain rich information on player behavior and thus have been widely analyzed by coaches and analysts to improve the players' performance. However, existing visual analytics systems often present the trajectories in court diagrams that are abstractions of reality, thereby causing difficulty for the experts to imagine the situation on the court and understand why the player acted in a certain way. With recent developments in immersive technologies, such as virtual reality (VR), experts gradually have the opportunity to see, feel, explore, and understand these 3D trajectories from the player's perspective. Yet, few research has studied how to support immersive analysis of sports data from such a perspective. Specific challenges are rooted in data presentation (e.g., how to seamlessly combine 2D and 3D visualizations) and interaction (e.g., how to naturally interact with data without keyboard and mouse) in VR. To address these challenges, we have worked closely with domain experts who have worked for a top national badminton team to design ShuttleSpace. Our system leverages 1) the peripheral vision to combine the 2D and 3D visualizations and 2) the VR controller to support natural interactions via a stroke metaphor. We demonstrate the effectiveness of ShuttleSpace through three case studies conducted by the experts with useful insights. We further conduct interviews with the experts whose feedback confirms that our first-person immersive analytics system is suitable and useful for analyzing badminton data.