Two weeks ago, I talked about the rise in sales of video-enabled mobile devices and how consumers now expect exceptional quality since they are paying extra for premium services. But how can video quality really be measured?
Traditional methods of measuring video quality focused around QoS, and usually involved some technical measure of network performance that dates back to voice technology. These methods may have been state-of-the-art in the past, but in today’s environment they can be inaccurate from a customer point of view, making them insufficient.
The historical way of measuring service quality has been to measure packet loss. For a voice call, with relatively steady packet transmission throughout the process, this was an acceptable measure of service quality. If a large percentage of packets were lost in transmission, the quality of the call was degraded significantly or lost entirely.
But video transmission is very different. In video content that contains fast action (a fast-paced sporting event, for example), even the loss of 1% of packets will produce a video that most consumers will perceive as poor and unacceptable for viewing. On the other hand, a video with little motion (a “talking head” during a newscast, for example) may have a much higher percentage of packet loss with no noticeable degradation in quality. What matters is perceptual quality. The consumer wants video transmissions that it perceives to be of the best quality, regardless of what a network-based statistical measure may conclude.
To measure perceptual quality, the focus shifts from Quality of Service (QoS) of the network to Quality of Experience (QoE) of the user. Whatever the content or setting, whether sporting events being viewed live, on-demand programming, or video-based advertising or political campaigns, consumers are demanding high quality video. The crux of a QoE solution is to identify a specific piece of video content and track it as it is transmitted through the network, perceiving quality as would the human eye and assigning higher importance to things (e.g., motion) to which the human eye is naturally attracted and lower importance to areas less likely to be noticed.
Measuring quality in this way enables network providers to quickly correct any network deficiencies, and in doing so, differentiate their services to open avenues toward additional monetization options.
Next week I’ll talk about how operators can benefit from measuring perceptual video quality on their networks. If you’re interested in learning more, check out Dialogic's new white paper.