Seven & i has been granted a patent for a system that captures images to train an item identification model. The system utilizes rotating platforms and multiple cameras to capture images of items, extracting features and associating them with identifiers to enhance the training dataset for improved item recognition. GlobalData’s report on Seven & i gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Seven & i, was a key innovation area identified from patents. Seven & i's grant share as of July 2024 was 49%. Grant share is based on the ratio of number of grants to total number of patents.

Image capture system for item identification model training

Source: United States Patent and Trademark Office (USPTO). Credit: Seven & i Holdings Co Ltd

The patent US12073623B2 describes a sophisticated system and method for capturing images to train an item identification model. Central to this system is a rotating platform equipped with multiple cameras and a 3D sensor. The cameras are strategically positioned to capture both overhead and perspective images of items placed on the platform. When a user places an item on the platform, the system detects this triggering event, rotates the platform, and captures images while doing so. The processor then extracts features from these images, such as dominant colors, dimensions, and contours, and associates them with an identifier for the item. This information is subsequently added to a training dataset for the item identification model.

Additionally, the system includes a weight sensor to measure the weight of items, allowing the processor to calculate and associate the mean weight of multiple instances of the same item with the training data. The cameras are arranged in specific configurations, including a triangular formation for overhead imaging and vertical arrangements for perspective views. The platform's rotation is precise, capturing images at incremental degrees to ensure comprehensive coverage of the item. This innovative approach enhances the training dataset's quality, ultimately improving the accuracy of the item identification model.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.