Video Content Analysis for Unattended Object Detection
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Solution Overview
Problem
Current video surveillance systems are inefficient in detecting suspicious objects and behaviors in real-time due to reliance on human intervention, which is prone to fatigue and lack of concentration, and fail to identify linked events or provide automated alerts, especially in high-security areas like airports and city centers.
Innovation Solution
A video content analysis-based system that processes video frames to detect differences, track objects, and generate alarms for suspicious behavior patterns, including unattended luggage or vehicles in restricted zones, using a multi-layered approach with preprocessing, object clustering, and scene characterization to automate the detection process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human security personnel are increased to detect suspicious objects, then detection coverage is improved, but operational cost and human fatigue increase
Solution Approach 1:
The surveillance system performs self-service by automatically detecting suspicious objects, tracking their movement, and generating alarms without requiring continuous human intervention. The system monitors itself through automated video analysis algorithms that identify suspicious patterns, thereby eliminating the need for large numbers of human operators while maintaining high detection coverage.
Solution Approach 2:
The patent replaces the mechanical human-centric detection system with an automated electronic surveillance system using video cameras and computer vision algorithms. This substitution eliminates human fatigue and operational costs while maintaining or improving detection reliability through consistent automated monitoring of suspicious objects and behaviors.
2Reliability
If human security personnel continuously monitor video feeds, then suspicious events are detected, but human fatigue and lack of concentration reduce efficiency
Solution Approach 1:
The surveillance system automatically performs the detection function without human intervention. The video analysis algorithms continuously process camera feeds, identify suspicious objects, track their movement patterns, and generate alarms autonomously. This self-service capability eliminates human fatigue while maintaining high detection efficiency through automated real-time monitoring.
Solution Approach 2:
The automated system provides continuous uninterrupted monitoring of suspicious objects and behaviors. Unlike human operators who experience fatigue and require breaks, the automated system maintains constant vigilance, continuously analyzing video feeds and tracking object movements without degradation in detection efficiency over time.
3Reliability
If manual alarm generation and distribution is used, then alarm situations are handled, but response time is delayed
Solution Approach 1:
The system maintains continuous automated monitoring and alarm generation capabilities. When suspicious objects or behaviors are detected, alarms are automatically generated and distributed in real-time without manual intervention delays. This continuous automated process ensures immediate response to security threats, eliminating the time loss associated with manual alarm handling procedures.
Solution Approach 2:
The patent replaces manual alarm generation and distribution with automated electronic systems. The video analysis algorithms automatically detect suspicious events, generate digital alarms, and distribute them through electronic communication channels instantaneously. This substitution eliminates the manual time-consuming processes of alarm generation and distribution while maintaining reliable alarm handling.
4Reliability
If current surveillance systems are used, then basic monitoring is provided, but linked events and suspicious patterns are not identified
Solution Approach 1:
The system merges multiple video feeds and detection algorithms into a unified surveillance platform. By combining video analysis, object tracking, and pattern recognition capabilities, the system identifies linked events and suspicious behaviors that individual monitoring systems would miss. This integration maintains basic monitoring while adding advanced analytical capabilities to detect complex threat patterns.
Solution Approach 2:
The patent introduces an intermediary layer of intelligent video analysis algorithms between the raw video feeds and the monitoring output. This intermediary layer processes video data to identify suspicious objects, track their movement, and detect linked events, thereby preventing loss of critical information while maintaining the basic monitoring function.
Data Source
AI summary
A surveillance system and method for the automatic detection of potential alarm situation via a recorded surveillance content analysis and for the management of the detected unattended object situation. The system and method are operative in capturing surveillance content, analyzing the captured content and providing in real time a set of alarm messages to a set of diverse devices. The system provides event based debriefing according to captured objects captured by one or more cameras covering different scenes. The invention is implemented in the context of unattended objects (such as luggage, vehicles or persons), parking or driving in restricted zones, controlling access of persons into restricted zones, preventing loss of objects such as luggage or persons and counting of persons.