Shopping Cart Video Inspection for Unscanned Item Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional transaction terminal systems fail to accurately detect items left in shopping carts, leading to financial losses for retailers as customers may not pay for items not placed on the conveyor belt, and existing video surveillance methods are time-intensive and burdensome for security personnel.
Innovation Solution
The Cart Inspector analyzes video data to identify suspicious transactions by comparing target images of shopping carts with reference representations of empty or non-suspicious carts, adjusting suspicion levels based on item location, shape, color, and characteristics, and generates notifications for transactions exceeding a threshold suspicion level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional transaction terminal systems are used to detect items left in shopping carts, then the system structure remains simple, but the detection accuracy is insufficient leading to financial losses
Solution Approach 1:
The patent replaces manual visual inspection by operators with automated video analysis systems. Video cameras capture images of shopping carts, and image processing algorithms automatically detect items left in carts, substituting mechanical human observation with automated optical and computational systems to improve detection accuracy while managing complexity through software automation.
Solution Approach 2:
The system creates visual copies (images) of shopping carts and their contents through video cameras. These image copies are then analyzed by processing algorithms to detect items left in carts, allowing accurate detection without requiring physical inspection of each cart, thus improving measurement precision while keeping the physical system relatively simple.
2Reliability
If video surveillance methods are used to monitor transactions, then detection capability is improved, but the time and effort required for security personnel to review footage increases significantly
Solution Approach 1:
The system performs preliminary automated analysis of video footage to identify suspicious transactions before security personnel review them. Image processing algorithms pre-screen all transaction videos, flagging only those with potential issues (items left in carts), so security personnel only need to review pre-identified suspicious cases, dramatically reducing their review time while maintaining reliable monitoring.
Solution Approach 2:
The video analysis system performs self-service by automatically detecting and flagging suspicious transactions without requiring continuous human monitoring. The image processing algorithms independently analyze footage and generate alerts, making the system self-sufficient in initial detection while human personnel only intervene when the automated system identifies potential issues.
3Productivity
If automated video analysis is implemented to identify suspicious transactions, then productivity of security personnel is improved, but the device complexity increases due to image processing requirements
Solution Approach 1:
The patent replaces manual video review with automated image processing systems. Computer algorithms automatically analyze video frames, detect items in shopping carts, and identify suspicious transactions, substituting mechanical human review with automated computational analysis to improve productivity while managing complexity through software automation.
Solution Approach 2:
The system creates digital copies of video frames and processes these image copies through automated algorithms. By working with image data copies rather than requiring human observers to watch original footage, the system achieves high productivity through automated analysis while the complexity is contained within the software processing layer.
Data Source
AI summary
Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area.The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.