Motion-Triggered Item Identification for Failed Barcode Scans
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Solution Overview
Problem
Checkout systems struggle with transactions when barcodes on items are damaged or obfuscated, leading to failed scans and transaction delays or abandonment of items.
Innovation Solution
A system that uses computer vision to detect incorrect barcode scans by monitoring user motions and triggers an item identification process, activating secondary cameras to capture and analyze images for item recognition, thereby adding the item to the transaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the item identification system is continuously activated to identify items with damaged barcodes, then the success rate of item identification improves, but the computing resource usage and power consumption increase
Solution Approach 1:
The system performs preliminary detection of barcode quality before activating the full item identification process. The computer vision system first checks if a barcode is detectable and assesses its quality, then only triggers the more resource-intensive item identification process when the barcode is found to be damaged or obfuscated, avoiding unnecessary activation when barcodes are clear
Solution Approach 2:
The system uses periodic monitoring of barcode scan attempts and user motions to detect potential issues. Instead of continuous full identification, the system periodically checks for scan failures and user corrective actions, activating the identification system only when needed based on these periodic observations
2Reliability
If the item identification system is continuously activated to identify items with damaged barcodes, then the success rate of item identification improves, but the power consumption increases
Solution Approach 1:
The system performs preliminary detection of barcode quality before activating the full item identification process. The computer vision system first checks if a barcode is detectable and assesses its quality, then only triggers the more resource-intensive item identification process when the barcode is found to be damaged or obfuscated, avoiding unnecessary activation when barcodes are clear
Solution Approach 2:
The system uses periodic monitoring of barcode scan attempts and user motions to detect potential issues. Instead of continuous full identification, the system periodically checks for scan failures and user corrective actions, activating the identification system only when needed based on these periodic observations
3Measurement precision
If the system monitors user motions continuously to detect incorrect barcode scans, then the detection accuracy improves, but the computing resource usage increases
Solution Approach 1:
The system monitors user motions periodically rather than continuously, analyzing video frames at intervals to detect corrective motions such as picking up items or approaching shelves. This periodic monitoring maintains detection accuracy for significant user actions while reducing the computational load compared to continuous frame-by-frame analysis
Solution Approach 2:
The system extracts only the essential motion patterns that indicate incorrect scans, such as specific hand movements or body orientations, rather than analyzing all video data. This selective extraction of relevant motion features maintains detection accuracy while minimizing computing resource usage
Data Source
AI summary
The present disclosure describes a computer system and method for motion activated item identification. The computer system includes a memory and a processor communicatively coupled to the memory. The processor detects, based on a video of a user, a motion of the user while scanning a barcode of an item and in response to determining, based on the motion of the user, that the barcode scanned incorrectly, captures an image of the item. The processor also determines, based on the image of the item, an identity of the item and adds, based on the identity of the item, the item to a checkout transaction.