Shelf Image Watermark Decoding Using Photogrammetry Calibration
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Solution Overview
Problem
Manual checking of store shelves for compliance with planograms is labor-intensive and time-consuming, and existing automated systems face challenges in accurately determining the scale and orientation of digital watermarks on products, leading to inefficiencies in inventory management and planogram compliance.
Innovation Solution
Employing photogrammetry techniques to determine the number of pixels per inch in captured images, allowing for quick rescaling of imagery to an optimal resolution for watermark decoding, and using shelf labels as calibration tools to simplify the detection of digital watermarks by establishing the angular field of view and distance, thereby enhancing the accuracy and speed of inventory tracking and planogram compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If photogrammetry techniques are employed to determine pixels per inch and rescale imagery, then watermark decoding accuracy is improved, but computational burden and processing time increase
Solution Approach 1:
The system performs photogrammetry calculations and imagery rescaling before watermark decoding, preparing the images in advance at optimal resolution. This preliminary preparation ensures accurate watermark detection while allowing the actual decoding process to run more efficiently on pre-processed images.
Solution Approach 2:
The processing pipeline is divided into distinct stages: photogrammetry-based scale determination, image rescaling to optimal resolution, and watermark decoding. This segmentation allows each stage to be optimized independently and enables parallel processing where applicable, reducing overall processing time.
2Measurement precision
If digital watermark technology is employed for product identification, then inventory tracking accuracy is improved, but device complexity and implementation difficulty increase
Solution Approach 1:
The system introduces an intermediary processing layer that handles photogrammetry calculations and image rescaling between image capture and watermark decoding. This intermediary layer simplifies the overall system by centralizing complex transformations and providing standardized pre-processed input to the watermark decoder.
Solution Approach 2:
The system dynamically adjusts image resolution and scaling parameters based on photogrammetry-derived measurements of pixels per inch. By changing these parameters adaptively rather than using fixed values, the system achieves high accuracy across varying camera positions and angles without requiring multiple specialized devices.
3Speed
If shelf labels are used as calibration tools, then detection speed is improved, but loss of information about actual product inventory increases
Solution Approach 1:
The system separates the calibration function (using shelf labels for scale and orientation reference) from the inventory detection function (identifying and counting products). This segmentation allows shelf labels to be used purely for geometric calibration without interfering with product identification, enabling both speed and information retention.
Solution Approach 2:
The system uses shelf labels as reference copies with known geometric properties to establish the camera's angular field of view and distance measurements. These label copies serve as calibration standards that provide scale information without replacing or obscuring the actual product inventory information needed for tracking.
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
This approach significantly reduces the computational burden and time required for watermark decoding, achieving high accuracy in inventory management and planogram compliance, allowing for real-time analysis and efficient identification of product placements and stock levels.
Implementation Method 1
capture imagery of every product on every shelf
Implementation Method 2
Employing photogrammetry techniques to determine the number of pixels per inch in captured images, allowing for quick rescaling of imagery
Data Source
AI summary
Imagery captured by an autonomous robot is analyzed to discern digital watermark patterns. In some embodiments, identical but geometrically-inconsistent digital watermark patterns are discerned in an image frame, to aid in distinguishing multiple depicted instances of a particular item. In other embodiments, actions of the robot are controlled or altered in accordance with image processing performed by the robot on a digital watermark pattern. The technology is particularly described in the context of retail stores in which the watermark patterns are encoded, e.g., on product packaging, shelving, and shelf labels. A great variety of other features and arrangements are also detailed.