Image-Based Planogram Product Space Detection for Automated Updates
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Solution Overview
Problem
Existing retail and distribution systems lack efficient methods for automatically creating and updating planograms that indicate the locations of products within facilities, requiring manual intervention and leading to inaccuracies in inventory management and customer guidance.
Innovation Solution
Utilizing cameras to capture images of product spaces, segmenting and identifying product groups, and determining their physical coordinates through image analysis and triangulation, allowing for the creation and continuous updating of planograms without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to create and update planograms, then accuracy in product location tracking can be maintained through human verification, but the process requires significant human intervention and time consumption
Solution Approach 1:
The system enables automated planogram creation and updating through self-service mechanisms where cameras capture images, image processing algorithms automatically identify product locations and group products, and the planogram is continuously updated without human intervention. The system serves itself by using the captured images and processed data to maintain accurate product location tracking autonomously.
Solution Approach 2:
Manual mechanical processes of creating and updating planograms are replaced with an automated optical and computational system. Cameras capture images of product spaces, image processing algorithms analyze the images to identify product groups and their locations, and the system automatically updates the planogram data structure, substituting human manual work with automated technological processes.
2Productivity
If automated image processing is implemented to track product locations, then real-time updates and productivity are improved, but system complexity increases
Solution Approach 1:
The image processing system is divided into distinct functional segments: camera modules capture images of product spaces, image processing algorithms segment the images to identify product groups, triangulation processes calculate physical coordinates, and planogram update modules integrate the data. This segmentation allows each component to perform its specific function efficiently while reducing overall system complexity through modular design.
Solution Approach 2:
The automated system performs multiple functions using integrated components: cameras capture images for both product location identification and verification, image processing algorithms simultaneously identify product groups and determine their locations, and the system continuously updates the planogram data structure. This multi-functionality improves productivity by consolidating multiple operations into a single automated workflow.
3Measurement precision
If multiple cameras are used to capture overlapping images for triangulation, then measurement precision of product coordinates is improved, but device complexity and cost increase
Solution Approach 1:
Multiple cameras are merged into a coordinated imaging system where their overlapping fields of view are combined through image processing. The system merges images from different camera angles, processes them together to identify product groups, and uses triangulation to calculate precise three-dimensional coordinates. This merging approach improves measurement precision by leveraging multiple perspectives while managing complexity through integrated processing.
Solution Approach 2:
Image processing algorithms serve as intermediaries that bridge multiple cameras and the final product location data. The intermediary processing system captures images from multiple cameras, performs segmentation to identify product groups, executes triangulation calculations to determine coordinates, and integrates the results into the planogram. This intermediary layer manages the complexity of multiple cameras while delivering precise measurement results.
Data Source
AI summary
This disclosure describes techniques for updating planogram data associated with a facility. The planogram may indicate inventory locations within the facility for various types of items supported by product fixtures. In particular an image of a product fixture is analyzed to identify image segments corresponding to product groups, where each product group consists of instances of the same product and each image segment corresponds to a group of image points. Image data is further analyzed to determine coordinates of the points of each image segment. A product space corresponding to the product group is then defined based on the coordinates of the points of the product group. In some cases, for example, a product space may be defined in terms of the coordinates of the corners of a rectangular bounding box or volume.