Fixed Retail Scanner With Real-Time Annotated Video Output
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Solution Overview
Problem
Existing data reading devices in retail environments lack the capability to provide annotated video data to external systems, limiting the functionality and analysis that can be performed on captured images.
Innovation Solution
A fixed retail scanner with a bioptic configuration, incorporating multiple imagers in horizontal and vertical housings, generates annotated image data by adding tags, distance measurements, and object information, which can be selectively transmitted to external systems based on real-time events or criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a fixed retail scanner captures and transmits raw image data to external systems, then the external systems can perform analysis, but the data transmission volume and processing burden increase significantly
Solution Approach 1:
The scanner performs preliminary actions by capturing images, detecting objects, generating annotations, and computing metrics before transmission. This preliminary processing at the scanner reduces the data volume that needs to be transmitted while preserving the essential information needed for external analysis.
Solution Approach 2:
The scanner extracts only the most relevant information from captured images by generating annotations that highlight key objects, attributes, and metrics. Instead of transmitting entire image datasets, the system extracts and transmits only the essential annotated data points that external systems need for analysis.
2Measurement precision
If the scanner processes and annotates all captured images locally, then the quality of transmitted data improves, but the scanner's processing requirements and complexity increase
Solution Approach 1:
The scanner performs partial processing by selectively annotating only certain objects or features in images based on predefined criteria or detection confidence levels. This partial annotation approach maintains data quality for critical information while reducing the overall processing burden and power consumption.
Solution Approach 2:
The annotation processing applies different levels of detail and processing intensity to different regions or objects within images based on their importance. Critical objects receive detailed annotation while less important areas receive minimal or no annotation, optimizing the balance between data quality and processing resources.
3Loss of information
If the scanner transmits all image data continuously, then external systems have complete information for analysis, but the network bandwidth and transmission efficiency are reduced
Solution Approach 1:
The system extracts and transmits only the essential annotated information rather than continuous streams of raw image data. This extraction approach maintains data availability for external analysis while dramatically improving transmission efficiency by sending only the most relevant information.
Solution Approach 2:
Instead of continuous transmission, the scanner transmits annotated data periodically or event-driven based on detection confidence, object importance, or predefined intervals. This periodic transmission maintains information availability while optimizing network bandwidth utilization.
4Area of stationary object
If the scanner includes multiple imagers for comprehensive coverage, then the field of view and detection capability improve, but the device complexity and cost increase
Solution Approach 1:
The scanner merges data from multiple imagers through a common processing pipeline that generates unified annotations across all views. This merging approach provides comprehensive field of view coverage while managing system complexity through integrated processing rather than separate independent systems.
Solution Approach 2:
The annotation system serves multiple functions simultaneously by processing images from different imagers, detecting various object types, and generating comprehensive annotations that work across all camera views. This multi-functionality justifies the complexity of having multiple imagers by providing versatile detection and annotation capabilities.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables enhanced image analysis and real-time annotation of captured data, allowing for improved object recognition, security checks, and analytics, and facilitating seamless integration with POS systems and remote analysis.
Implementation Method 1
converting light reflected from a target into image data utilizing an image sensor
Data Source
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AI summary
A fixed retail scanner comprises imagers configured to capture image data, and a processor operably coupled to the imagers. The processor is configured to provide image data from at least some of the imagers in real-time during a transaction to a decoder within the data reader for decoding an optical code on an object within the image data, generate annotations for the image data based on an analysis of image content of the image data to generate annotated image data, and provide the annotated image data from at least some of the imagers to an external system in real-time during the transaction.