Shopping Cart Video Inspection for Omitted 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 retail establishments due to the reliance on human observation, which is time-intensive and inefficient, and require additional camera systems that are burdensome and redundant with existing security setups.
Innovation Solution
The Cart Inspector system performs video analysis to identify suspicious transactions by comparing target images with reference representations of non-suspicious activity, adjusting suspicion levels based on item location, shape, color, and characteristics, and provides real-time notifications when the threshold suspicion level is surpassed, allowing retailers to efficiently locate potential discrepancies in video footage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional transaction terminal systems rely on human observation to detect items left in shopping carts, then the system is simple to operate, but the detection accuracy is low and time-consuming
Solution Approach 1:
The patent replaces manual visual inspection by security personnel with an automated computer vision system that uses image processing algorithms to detect items left in shopping carts. The system automatically analyzes video footage from existing cameras, identifies suspicious transactions, and generates alerts, thereby eliminating the time-consuming manual review process while significantly improving detection accuracy.
2Measurement precision
If additional camera systems are installed to improve item detection, then the detection capability is enhanced, but the device complexity and cost increase
Solution Approach 1:
The patent makes the existing security camera system multi-functional by enabling it to perform both its original security monitoring function and the new function of detecting items left in shopping carts. The same cameras and processing infrastructure are used for both purposes, eliminating the need for additional dedicated camera systems and reducing overall system complexity.
Solution Approach 2:
The patent merges the item detection functionality with the existing security surveillance system. By combining these functions into a single integrated system, the patent avoids the complexity and cost of deploying separate camera systems, while still achieving enhanced detection capability through sophisticated image analysis algorithms.
3Reliability
If security personnel manually review all video footage to find omitted items, then comprehensive detection is possible, but the productivity is low
Solution Approach 1:
The patent extracts and isolates only the suspicious transactions from the entire video footage using automated image analysis. Instead of requiring personnel to review all video frames, the system identifies and flags only those transactions where items were likely left in carts, generating a condensed list of suspects for further review. This extraction approach maintains comprehensive detection while dramatically improving review efficiency.
Solution Approach 2:
The patent implements a feedback mechanism where the automated system continuously analyzes video footage, compares detected items with transaction records, and refines its detection algorithms based on identified patterns. This feedback loop improves detection accuracy over time while maintaining high productivity, as the system becomes increasingly efficient at identifying suspicious transactions without requiring proportional increases in review time.
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.