Video Highlight Tagging via Preliminary Action
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Solution Overview
Problem
Existing video recording technologies require users to view entire event recordings to find specific highlights, lacking efficient mechanisms for creating and sharing personalized moments, which is time-consuming and inconvenient for spectators and coaches.
Innovation Solution
A method and system that allow users to receive a video stream from a camera, generate and store tags for specific portions of the stream, enabling the creation of personalized highlights and video clips, which can be shared with others, using client devices and a server for tagging and grouping tags.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users view the entire event recording to find specific highlights, then they can locate desired moments, but it consumes excessive time and is inconvenient
Solution Approach 1:
The system performs preliminary tagging of video portions during or immediately after the event, creating indexed markers before the user needs to view highlights. Users can directly jump to tagged portions without watching the entire recording, resolving the time loss while maintaining accurate highlight location.
2Adaptability or versatility
If users manually edit the entire recording to create highlights, then personalized moments can be created, but the process is time-consuming and complex
Solution Approach 1:
The system automatically tags portions of the video stream during the event based on detected events or user inputs at that moment. This preliminary tagging eliminates the need for time-consuming post-event editing while maintaining full personalization capability, as users can select from pre-tagged portions to create customized highlights.
Solution Approach 2:
The system automatically detects and tags event portions without requiring manual user intervention during the event. Multiple users can independently tag portions, and the system consolidates these tags to create highlights automatically, reducing the burden on individual users while maintaining versatility.
3Productivity
If multiple users tag moments simultaneously, then crowd-sourced highlights can be created, but system complexity increases
Solution Approach 1:
The server acts as an intermediary that receives tags from multiple user devices, consolidates them, and manages the tagging data centrally. This intermediary architecture enables multiple users to tag simultaneously without increasing complexity at individual devices, while the server handles the coordination and aggregation of crowd-sourced tags efficiently.
Data Source
AI summary
Implementations generally relate to providing highlights of an event recording. In some implementations, a method includes receiving, at a client device, a video stream associated with an event. The method further includes receiving, at the client device, one or more tag commands from a user. The method further includes generating one or more tags based on the one or more tag commands, where each tag of the one or more tags tags a portion of the video stream. The method further includes tagging one or more portions of the video stream based on the one or more tags. The method further includes storing a copy of the video stream and the one or more tags on the client device.