Beyond the Broadcast: Enhancing VR Tennis Broadcasting through Embedded Visualizations and Camera Techniques

TL;DR

This work targets VR tennis broadcasting, where camera language and embedded in-game visualizations are underdeveloped. It develops a tennis-specific design framework by analyzing 400 out-of-play clips and 25 cinematic VR animations, reconstructing match trajectories from monocular footage, and implementing Beyond the Broadcast, a VR viewing system that overlays dynamic visualizations with adaptive camera motion. The main contributions include a dual data-driven design framework, an end-to-end VR pipeline converting broadcast video into immersive VR with integrated visualizations, and a controlled user study showing improved comprehension, narrative engagement, and perceptual immersion without sacrificing comfort. The approach has practical impact on viewer experience and can be extended to other sports, offering a scalable path toward unified VR broadcasting that combines visualization-rich analytics with cinematic VR storytelling.

Abstract

Virtual Reality (VR) broadcasting has emerged as a promising medium for providing immersive viewing experiences of major sports events such as tennis. However, current VR broadcast systems often lack an effective camera language and do not adequately incorporate dynamic, in-game visualizations, limiting viewer engagement and narrative clarity. To address these limitations, we analyze 400 out-of-play segments from eight major tennis broadcasts to develop a tennis-specific design framework that effectively combines cinematic camera movements with embedded visualizations. We further refine our framework by examining 25 cinematic VR animations, comparing their camera techniques with traditional tennis broadcasts to identify key differences and inform adaptations for VR. Based on data extracted from the broadcast videos, we reconstruct a simulated game that captures the players' and ball's motion and trajectories. Leveraging this design framework and processing pipeline, we develope Beyond the Broadcast, a VR tennis viewing system that integrates embedded visualizations with adaptive camera motions to construct a comprehensive and engaging narrative. Our system dynamically overlays tactical information and key match events onto the simulated environment, enhancing viewer comprehension and narrative engagement while ensuring perceptual immersion and viewing comfort. A user study involving tennis viewers demonstrate that our approach outperforms traditional VR broadcasting methods in delivering an immersive, informative viewing experience.

Figures (5)

• Figure 1: Comparative analysis of annotated camera usage in VR narrative animations (left, purple) and traditional 2D tennis broadcasts (right, green). The right-side summarizes camera shot frequencies across narrative targets for three event categories, excluding repetitive angular pans focusing on player emotions. The left-side details corresponding VR annotations by shot size and camera motion type. Bar lengths represent normalized frequencies per side, with total counts provided. The comparison highlights differences: traditional broadcasts frequently utilize Close-Up shots and Angular motions to enhance emotional and tactical emphasis, whereas VR animations predominantly use Medium Shots with Static or Linear motions, optimizing narrative clarity and viewer comfort.
• Figure 2: Our design framework integrates camera configurations—defined by shot size, angle, and motion—to convey narrative and boost viewer engagement. Embedded visualizations further complement these configurations by emphasizing key match events, thereby enriching overall comprehension and ensuring that visual data is effectively conveyed through camera techniques.
• Figure 3: Overview of our system pipeline for converting raw broadcast footage into an immersive VR tennis experience. Dynamic tracking data, extracted from the footage, feeds into the visualization in Motion module to overlay real-time cues—such as ball trajectories and impact highlights. Simultaneously, simulated game data is aggregated to compute event metrics (e.g., ball bounce area placements), which are presented as static visualizations. Finally, adaptive camera motions integrate these components, guiding viewer attention and constructing a coherent narrative.
• Figure 4: Participants' ratings (1–5 Likert scale) for Comprehension, Engagement, Immersion, and Comfort across three conditions: Baseline, Visualization Only, and Full Integration. Results indicate notable improvements in Comprehension, Engagement, and Immersion with embedded visualizations and adaptive camera movements, while Comfort remains consistently high across conditions.
• Figure 5: Detailed survey responses for the Full Integration condition, showing participants' agreement levels (1–5 Likert scale) with individual statements related to Comprehension, Engagement, Immersion, and Comfort. Mean ($\mu$) and SD ($\sigma$) for each item are shown on the right.