Low delay video transmission is becoming increasingly important. Delay critical, video enabled applications range from teleoperation scenarios such as controlling drones or telesurgery to autonomous control through computer vision algorithms applied on real-time video. Two examples for this are autonomous driving and visual servoing, as depicted in the images below.


For such highly dynamic applications, the end-to-end (E2E) latency of the involved video transmission is critical. Therefore, we analyze the latency contributors in video transmission and research approaches to reduce latency. In our project, we first needed to measure the E2E latency with sub-millisecond precision. We define E2E latency as the time between an event first visisbly taking place in the field of view of the camera and the time when this event is first visibly represented on a display. We developed a system that can perform such a precise measurement in an automated, non-intrusive, portable and inexpensive manner, which no previous system could deliver.

Current work investigates improving the delay measurement system, the delay simulation of video transmission, analyzing the Rate-Distortion-Delay tradeoff in video coding, and a number of measures to reduce delay in video coding. Some of these methods are under patent application which is why we can not provide further details at this time.