Video Analysis System Using AI Intermediary for Security Monitoring
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Solution Overview
Problem
Existing security and surveillance systems face challenges in real-time monitoring and detection of events of interest due to the overwhelming amount of video data, leading to missed security events and compromised safety, as current video analysis techniques lack comprehensive and actionable intelligence.
Innovation Solution
A machine learning-based system that processes live video image data through coarse feature extraction, ensemble machine learning models for object and activity detection, and a natural language model to generate descriptive intelligence, enhancing real-time event detection and response capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple video cameras are deployed to monitor defined spaces, then coverage area increases, but the number of video feeds exceeds security personnel capacity to review them
Solution Approach 1:
The patent introduces an automated video analysis system with AI algorithms as an intermediary between the multiple video cameras and security personnel. This intermediary automatically processes video feeds, detects events of interest, and prioritizes alerts, enabling security personnel to effectively monitor coverage from many more cameras than previously possible.
Solution Approach 2:
The patent replaces the manual mechanical review process of security personnel with automated electronic video analysis systems. Machine learning models and computer vision algorithms automatically analyze video content, substitute human reviewers for the initial detection layer, and present only relevant findings to security personnel.
2Measurement precision
If discrete detection methods are used for specific object categories, then detection accuracy for that category improves, but comprehensive event understanding deteriorates
Solution Approach 1:
The patent merges multiple discrete detection models into a unified ensemble system. Different detection models for various object categories (person, vehicle, animal, etc.) are combined with activity recognition and relationship analysis models to provide comprehensive event understanding while maintaining high detection accuracy for each category.
Solution Approach 2:
The patent creates a universal video analysis platform that performs multiple functions: object detection, activity recognition, relationship analysis, and event synthesis. This multi-functional system handles diverse detection tasks within a single integrated framework, preventing information loss across different detection domains.
3Measurement precision
If video data is reviewed reactively after events occur, then thorough analysis is possible, but real-time security response is compromised
Solution Approach 1:
The patent implements preliminary action by continuously analyzing video data in real-time to detect events before they escalate. The system proactively identifies potential security threats, performs preliminary assessment and classification, and alerts personnel in advance, enabling preventive rather than reactive security responses.
Data Source
AI summary
A system and method for implementing a machine learning-based system for generating event intelligence from video image data that: collects input of the live video image data; detects coarse features within the live video image data; constructs a coarse feature mapping comprising a mapping of the one or more coarse features; receives input of the coarse feature mapping at each of a plurality of distinct sub-models; identify objects within the live video image data based on the coarse feature mapping; identify one or more activities associated with the objects within the live video image data; identify one or more interactions between at least two of the objects within the live video image data based at least on the one or more activities; composes natural language descriptions based on the one or more activities associated with the objects and the one or more interactions between the objects; and constructs an intelligence augmented live video image data.