Shrink Event Detection System Using Automated Video Analysis
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Solution Overview
Problem
Current methods for detecting shoplifting events in retail venues are dependent on the attentiveness of security personnel and often result in missed occurrences due to the dynamic nature of these events and limited visibility, leading to unrecognized shrinkage and item loss.
Innovation Solution
A shrink event detection system utilizing a network of sensing units with RFID, ultrasonic, and video systems to track and analyze movements of people and products, generating and updating templates based on detected attributes to alert security personnel of potential shoplifting events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If security personnel manually monitor video feeds and attempt to recognize shrink events, then human judgment and adaptability are applied, but the system reliability deteriorates due to human attentiveness limitations and inability to recognize events outside current view
Solution Approach 1:
The patent introduces an automated video analysis system with machine learning algorithms as an intermediary between the video feed and security personnel. This intermediary automatically analyzes video streams, detects shrink events, and generates alerts, eliminating the need for security personnel to manually monitor every event while maintaining high detection reliability through automated pattern recognition
Solution Approach 2:
The patent replaces the mechanical system of human visual monitoring with an automated electronic analysis system. The machine learning-based video analysis system processes video feeds, identifies suspicious behaviors, and detects shrink events without requiring continuous human attention, thereby improving reliability while preserving the adaptability of pattern recognition through trained algorithms
2Measurement precision
If security personnel focus on specific areas or events, then attention is concentrated on potential threats, but simultaneously occurring shrink events in other areas go unnoticed
Solution Approach 1:
The automated video analysis system performs multiple functions simultaneously: it monitors all video feeds across all areas, detects various types of shrink events, identifies suspicious behaviors, and generates alerts for multiple events concurrently. This multi-functional capability ensures comprehensive coverage without dividing security personnel's attention, resolving the contradiction between focused monitoring and comprehensive coverage
3Reliability
If automated systems are implemented to detect shrink events, then detection reliability improves through consistent monitoring, but device complexity increases due to advanced sensors and data processing requirements
Solution Approach 1:
The patent segments the automated detection system into distinct functional modules: video capture units, video analysis subsystems with machine learning algorithms, sensor networks, data processing components, and alert generation systems. Each module performs a specific function, making the overall complex system manageable through modular design while maintaining high detection reliability through consistent automated operation
Data Source
AI summary
In an embodiment, the present invention is a shrink event detection system for use within a venue. The system includes a server associated with a venue containing a plurality of items, the server including one or more processors, and a shrink event detection subsystem. The shrink event detection subsystem is operable to: detect a theft event of a stolen item; backtrack from the theft event of the stolen item to recognize at least one attribute related to the theft event; and record the at least one attribute in a tracking database, the tracking database being accessible by the server. The system is configured such that the server, via the one or more processors, generates a shrink event template based at least in part of the at least one attribute in the tracking database.