Video Identification System for Event Timestamping and Storage Optimization
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Solution Overview
Problem
In the context of video monitoring, it is challenging for users to distinguish important information from unimportant information in recorded videos, leading to missed critical events and inefficient storage usage due to the need for manual sorting through large datasets.
Innovation Solution
A video identification method and device that acquire and mark event information in videos with corresponding time stamps, utilizing modules for event detection, time point determination, and identification, enabling efficient browsing and storage optimization by highlighting important frames and allowing for easy retrieval of relevant information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all video data is stored for monitoring purposes, then complete record of events is achieved, but storage space consumption increases and user browsing efficiency deteriorates
Solution Approach 1:
The patent extracts and identifies key event information from the entire video dataset using image recognition and event detection algorithms. Only frames containing significant events are retained and marked, while redundant frames are removed or compressed, thus reducing storage space while preserving essential monitoring information.
Solution Approach 2:
The system discards unimportant video frames that do not contain significant events, and recovers only the essential event information by storing metadata and timestamps associated with identified events. This allows reconstruction of important events without storing complete video data.
2Loss of information
If manual sorting through video data is performed, then complete review of content is possible, but time consumption increases and user efficiency decreases
Solution Approach 1:
The system performs preliminary automatic analysis of video content during or immediately after recording, identifying and marking key events with timestamps and metadata before the user needs to review the footage. This preliminary processing eliminates the need for manual sorting during user browsing.
Solution Approach 2:
The patent introduces an intermediary event detection and identification system that acts as a mediator between the raw video data and the user. This intermediary layer processes video content automatically, extracts meaningful events, and presents them to users in an organized manner, eliminating direct manual sorting.
3Productivity
If event detection and identification systems are implemented, then browsing efficiency is improved, but device complexity increases
Solution Approach 1:
The patent implements a multi-functional integrated system where the monitoring device, event detection module, image recognition engine, and database management work together as a unified platform. This universal system performs multiple functions (monitoring, detection, recognition, storage, and retrieval) without requiring separate complex subsystems.
Solution Approach 2:
The system is designed to automatically detect, identify, and mark events without requiring manual intervention or complex external processing. The event detection algorithms and image recognition systems operate autonomously, making the system self-sufficient and reducing the need for additional complex infrastructure.
Data Source
AI summary
Method and devices are provided for video identification. The method may include following actions. Event information representative of an event occurring in a space where a monitoring device is located is acquired. A time point corresponding to the event information in a video shot by the monitoring device is determined, and the event information is identified at the time point in the video shot by the monitoring device.