Video Session Server Automatic Event Markering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for reporting and recording video streams in video sessions are inefficient, as users must manually view streams to identify interesting moments, and persistent real-time group chatrooms continue to exist even when no participants are active, leading to unnecessary resource usage and notifications being sent to inactive participants.
Innovation Solution
A computer server machine analyzes video streams to identify interesting events and generates markers for clients, allowing users to easily access these moments, and maintains a persistent real-time group chatroom that only notifies active participants of activity, ensuring efficient resource usage and relevant notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually view video streams to identify interesting moments, then they can find relevant content, but the process is time-consuming and inefficient
Solution Approach 1:
The system performs automatic analysis of video streams to identify interesting moments without requiring user intervention. The server autonomously processes video data, detects events, and generates markers, allowing the system to serve itself in the task of content identification rather than relying on manual user review.
Solution Approach 2:
The manual mechanical process of users watching and identifying interesting moments is replaced with an automated computer vision and event detection system. The server uses algorithms to analyze video streams, identify events, and create markers, substituting human manual review with automated computational analysis.
2Reliability
If the chatroom remains persistent with all participants, then everyone can be notified of activity, but resources are wasted on inactive participants
Solution Approach 1:
The chatroom system applies different states to different participants based on their activity status. Active participants receive full notification services while inactive participants are excluded from notification loops. This local differentiation of participant quality allows the system to optimize resource usage by treating active and inactive participants differently rather than uniformly.
Solution Approach 2:
The system performs partial notification actions by only notifying active participants rather than all participants. This partial action approach avoids the excessive resource consumption of notifying inactive users while still maintaining reliable notification delivery to those who can actually receive and act on notifications.
3Productivity
If notifications are sent to all participants including inactive ones, then comprehensive coverage is achieved, but irrelevant notifications are sent to users not actively using the service
Solution Approach 1:
The system performs preliminary identification of active participants before sending notifications. By determining which users are currently active in the chatroom before initiating notification delivery, the system prevents irrelevant notifications from being sent to inactive users while maintaining comprehensive coverage among the active user base.
Data Source
AI summary
In one embodiment, a computer server machine receives, from one or more client devices, one or more video streams associated with a video session associated with one or more users. The one or more users are respectively associated with each client device. The computer server machine analyzes the one or more video streams to identify an interesting event and generates a marker for the one or more video streams based on a time associated with the identified interesting event. The computer server machine sends information regarding the marker to the one or more client devices.