Live TV Streaming Latency Measurement Using YOLO

• Miguel Jose Esteve Broton ^[2] ; Miguel Angel Santiago Cabello ^[2] ; Jose Garcia-Rodriguez
  1. [1] Universitat d'Alacant

     Universitat d'Alacant

     Alicante, España

     
  2. [2] Telefonica I+D, Madrid, Spain
• Localización: Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence: 9th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, Puerto de la Cruz, Tenerife, Spain, May 31 – June 3, 2022, Proceedings, Part II / José Manuel Ferrández Vicente (dir. congr.) , José Ramón Álvarez Sánchez (dir. congr.) , Félix de la Paz López (dir. congr.) , Hojjat Adeli (aut.), 2022, ISBN 978-3-031-06527-9, págs. 203-212
• Idioma: inglés
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• Resumen

  • This paper proposes a simple yet effective approach to measure the e2e latency in the live video streaming pipeline, from when the signal is generated in the production studios until it is played on the client device. The method is based on user-centric behavior by looking at the time the content is produced in the source context and comparing it with the current clock time at the playback device. Given a clock timestamp introduced in the signal at the production stage, we rely on an intelligent streaming latency measurement agent that, first, detects with YOLO that mark at the playout device, then use an OCR to convert the bitmap text in the clock to a string text, and finally, compares it with the real-time clock in the machine, providing real-time end to end streaming latency. Our method, even simple, allows us to measure the latency on any playout device, as it does not rely on any in-band signaling but a human-centric behavior simulated by an intelligent measurement agent.