Network Device Video Highlight Generation from User Segment Ratings
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Solution Overview
Problem
Existing internet TV systems lack efficient methods for generating personalized video highlights that meet user preferences, consuming network resources and failing to provide timely, interactive experiences due to server-side processing and limited remote control interaction.
Innovation Solution
A network device that processes user evaluations from remote controllers to generate personalized video highlights based on metadata, allowing users to select and jump-play segments that match their preferences, reducing network load and enhancing interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If server-side processing is used to generate video highlights, then centralized control is achieved, but network resources are consumed and response time increases
Solution Approach 1:
The patent segments the highlight generation process into client-side evaluation (where users interact with the system) and server-side aggregation (where data is collected and processed). This segmentation allows the heavy processing to be distributed, reducing the burden on any single server while maintaining centralized coordination.
Solution Approach 2:
The system performs preliminary actions by pre-dividing video content into segments and pre-configuring evaluation types before actual viewing occurs. During playback, users simply provide evaluations for specific segments rather than processing the entire video, significantly reducing real-time network resources required.
2Extent of automation
If server-side processing is used to generate video highlights, then centralized control is achieved, but response time increases
Solution Approach 1:
By segmenting the video into discrete time segments and requesting evaluations only for those segments rather than processing the entire video stream in real-time, the system reduces the time required to generate highlights while maintaining centralized control through the server.
Solution Approach 2:
The system performs preliminary processing by pre-segmenting videos and pre-establishing evaluation frameworks before playback. During actual viewing, users provide evaluations for specific segments, and the server aggregates these pre-organized data points, significantly reducing response time compared to processing entire videos in real-time.
3Loss of information
If user evaluations are collected for all video segments, then comprehensive data is obtained, but network consumption increases
Solution Approach 1:
The system applies local quality by collecting and processing evaluation data specifically for video segments that are actually being viewed or are of interest to users, rather than attempting to collect data for all segments. This targeted approach maintains comprehensive data for relevant content while reducing overall network consumption.
Solution Approach 2:
The system uses partial action by requesting evaluations only for specific video segments rather than all segments. This partial collection of data maintains sufficient information for generating meaningful highlights while significantly reducing the network bandwidth and processing resources required.
4Ease of operation
If personalized highlights are generated based on user preferences, then user experience improves, but system complexity increases
Solution Approach 1:
The system applies universality by creating a multi-functional evaluation framework that can handle multiple evaluation types (e.g., quality, entertainment value, information density) through a unified processing architecture. This allows personalized highlights to be generated for different user preferences using the same core system components, reducing the need for separate specialized systems for each preference type.
Data Source
AI summary
Network device, method and computer-readable medium for video content processing. The network device comprises a memory having instructions stored thereon and a processor configured to execute the instructions stored on the memory to cause the network device to perform the following operations: Acquiring metadata of video content, wherein the video content comprises a plurality of segments, and the metadata represents evaluations from a plurality of users for at least one of the plurality of segments; according to the metadata and the preference information of the local users, generating highlights of the video content for the local users to play.


