Media Aware Network Elements for Dynamic Video Object Insertion
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Solution Overview
Problem
Current networking technologies face challenges in accommodating video application demands while reducing complexity and ensuring an enjoyable user experience, particularly due to limitations in hardware and software capabilities of endpoints for dynamic insertion and removal of video objects, such as language translations and location-based processing, which are often difficult to perform at endpoints due to significant processing and communication overhead.
Innovation Solution
The implementation of Media Aware Network Elements (MANEs) with Insertion/Removal (IR) modules that dynamically insert or remove video objects within the network, leveraging central knowledge of the network to process media streams, including converting speech to text, adding timestamps, and inserting or removing advertisements, thereby enhancing media processing capabilities and enabling consistent quality of experience across endpoints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video processing is performed at endpoints, then video application demands can be accommodated, but processing complexity and communication overhead increase significantly
Solution Approach 1:
The patent introduces a network-based video processing system that acts as an intermediary between video sources and endpoints. This mediator performs complex video processing operations (insertion, removal, translation of video objects) in the network infrastructure rather than at endpoints, reducing endpoint complexity while maintaining adaptability to various video applications
2Productivity
If dynamic insertion and removal of video objects is performed at endpoints, then media processing capabilities are enhanced, but processing overhead and communication costs increase
Solution Approach 1:
The system relocates the processing workload from endpoints to a network-based intermediary that handles dynamic insertion and removal of video objects. This reduces the processing overhead at endpoints while maintaining enhanced media processing capabilities through the network infrastructure
Solution Approach 2:
The system performs video processing operations in advance within the network infrastructure before video content reaches endpoints. By preliminarily processing video streams (inserting advertisements, translating video objects, removing content) in the network, the system reduces the need for high-performance processing at endpoints
3Adaptability or versatility
If language translation and location-based processing are performed at endpoints, then user experience is personalized, but processing requirements and communication overhead become significant
Solution Approach 1:
The network-based system acts as a mediator that performs language translation and location-based processing operations before video content reaches endpoints. This intermediary approach enables personalized user experience (different languages, location-specific content) while reducing communication overhead and processing requirements at endpoints
Data Source
AI summary
An example method may include receiving a media stream from a first endpoint, where the media stream is intended for a second endpoint; processing the media stream according to at least one processing option; compressing the media stream; and communicating the media stream to the second endpoint. In more specific instances, the processing may include converting a speech in the media stream to text in a first language; converting the text in the first language to text in a second language; rendering the text in the second language; and adding the rendered text in the media stream.