The crowd as a cameraman: on-stage display of crowdsourced mobile video at large-scale events

Abstract

Recording videos with smartphones at large-scale events such as concerts and festivals is very common nowadays. The se videos register the atmosphere of the event as it is experienced by the crowd and offer a perspective that is hard to capture by the professional cameras installed throughout the venue. In this article, we present a framework to collect videos from smartphones in the public and blend these into a mosaic that can be readily mixed with professional camera footage and shown on displays during the event. The video upload is prioritized by matching requests of the event director with video metadata, while taking into account the available wireless network capacity. The proposed framework's main novelty is its scalability, supporting the real-time transmission, processing and display of videos recorded by hundreds of simultaneous users in ultra-dense Wi-Fi environments, as well as its proven integration in commercial production environments. The framework has been extensively validated in a controlled lab setting with up to 1 000 clients as well as in a field trial where 1 183 videos were collected from 135 participants recruited from an audience of 8 050 people. 90 % of those videos were uploaded within 6.8 minutes.

Visual Perception Enabled Industry Intelligence: State of the Art, Challenges and Prospects

“…Participants can review the entire event from different perspectives through information provided by others. Bohez et al [140] introduced an integrated framework to mix users phones shooting perspectives with professional camera lenses and displayed during the event. The framework could transmit, process, and display hundreds of user videos in real time in an ultra-dense Wi-Fi environment.…”

“…Social [139] Health [135] Smart City [131], [137] Architecture [130] Navigation [131], [133], [134] Rescue [136] Image or video information fusion [132], [140] Event location [139] Event matching and clustering [138] Crowdsourcing analysis [141] Object Pose Measurement…”

Performance Analysis of Mobile Video Networks

“…Based semi-blind video watermarking algorithm, [2] proposed a robust block classification to enhance the robustness performance. In [3], the authors presented a framework to collect videos from smartphones in the public.…”