Cloud-Based TV UI Latency Measurement With Frame Metadata
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for measuring cloud-based TV user interface rendering latency lack a direct way to associate client inputs with corresponding video frames, requiring special hardware and manual video analysis, which is impractical for low-cost client devices.
Innovation Solution
A method that involves tagging client inputs in the cloud before rendering, associating the input events with rendered frames, and inserting metadata in the frame headers to enable accurate end-to-end latency measurement without client-side hardware or manual processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If client-based solutions are used to measure latency, then measurement capability is provided, but special hardware and manual video analysis are required which makes it impractical for low-cost client devices
Solution Approach 1:
The patent introduces cloud-based intermediaries (servers) that receive client inputs, render UI frames, and insert metadata to associate inputs with rendered frames. This mediator system eliminates the need for complex client-side hardware and manual analysis by performing latency measurement functions in the cloud instead.
Solution Approach 2:
The patent replaces manual video analysis with automated cloud-based processing. Instead of requiring manual examination of video frames on client devices, the system automatically processes inputs, renders frames, extracts metadata, and calculates latency in the cloud, substituting mechanical manual operations with automated digital processing.
2Extent of automation
If cloud-based rendering is used, then processing is centralized, but there is no direct way to associate client inputs with corresponding video frames for latency measurement
Solution Approach 1:
The patent applies preliminary action by inserting metadata into rendered frames before they are sent to client devices. This metadata contains information about the associated input event (such as timing data), allowing the client to later correlate the input with the rendered frame and calculate latency without requiring complex association mechanisms.
Data Source
AI summary
Techniques for measuring cloud-based input latency are described herein. In accordance with various embodiments, a server including one or more processors and a non-transitory memory receives from a client an input event corresponding to a request for a TV user interface (UI). The server adds a tag to each of a set of screens corresponding to the TV UI and records event data corresponding to the input event prior to rendering the set of screens into a set of rendered frames. The server additionally decodes the tag in the set of rendered frames to generate metadata that associate the event data with the set of rendered frames prior to encoding the set of rendered frames into a set of encoded frames. The server also transmits to the client the set of encoded frames and the metadata.