Computer Vision Planogram Generation via Image Detection
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Solution Overview
Problem
Conventional planogram generation systems are not facility-specific, lack automation, and are inefficient due to manual processes, high costs, and human error, failing to dynamically reflect customer and facility data, and real-time transmission to central entities.
Innovation Solution
A system and method that uses image detection and processing to associate items with labels, identify attributes, and determine positions, enabling automatic and dynamic planogram generation and modification, utilizing a mobile device with imaging assembly and processor to create facility-specific planograms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual planogram generation is used, then flexibility and adaptability are maintained, but productivity and efficiency deteriorate
Solution Approach 1:
The system enables self-service through automated image recognition and processing. The mobile device captures images of shelves and products, and the system automatically generates planograms without requiring manual intervention from associates, thereby maintaining adaptability while significantly improving efficiency
Solution Approach 2:
The patent replaces manual mechanical processes with automated computer vision systems. Image processing algorithms and machine learning models substitute for human analysts manually creating planograms, eliminating the trade-off between flexibility and efficiency
2Productivity
If automated image processing is used, then productivity is improved, but device complexity increases
Solution Approach 1:
The mobile device serves multiple functions: capturing images, processing images, generating planograms, and communicating with central entities. This multi-functionality consolidates what would otherwise require separate complex systems into a single device, improving productivity without proportionally increasing complexity
Solution Approach 2:
The system uses an intermediary processing layer that simplifies the connection between image capture and planogram generation. This intermediary layer handles the complexity of image processing and data transmission, allowing the mobile device to maintain simplicity while achieving automated productivity
3Reliability
If real-time transmission to central entity is implemented, then responsiveness is improved, but loss of time in transmission increases
Solution Approach 1:
The system implements periodic transmission of planogram data to central entities rather than continuous transmission. This allows real-time responsiveness for facility-specific optimizations while minimizing transmission time and data transfer overhead by sending updates only when necessary
Data Source
AI summary
Devices and methods for planogram generation are disclosed herein. The method detects at least one first item and at least one label present in a captured image and associates the at least one first item with the at least one label based on a boundary between the at least one first item and at least one second item different from the at least one first item. The method identifies the at least one first item based on at least one attribute of the at least one first item and determines an area indicative of a position of the identified at least one first item based on the association. The area can be one or more of an aisle, a module, a shelf, a rack, a bay, and a bin. The method generates a planogram based on the association, the identified at least one first item and the area.