Item Height Confirmation for Real-Time Visual Identification
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Solution Overview
Problem
Identifying and tracking multiple items in real-time is computationally intensive and time-consuming, making it incompatible with real-time applications, and maintaining accuracy in item identification and tracking is challenging due to potential shifts in camera, 3D sensor, and platform positions.
Innovation Solution
A system using 3D sensors and cameras to capture images, identify items, and recalibrate cameras and 3D sensors based on updated homographies to maintain accuracy, along with techniques for detecting triggering events and item placement, reducing search space through container categorization, and utilizing item height for confirmation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional item identification methods are used to identify and track multiple items, then item identification can be performed, but the process is computationally intensive and time-consuming, making it incompatible with real-time applications
Solution Approach 1:
The patent segments the item identification process into distinct stages: first capturing images of multiple items, then identifying items in sequence from the captured images. This segmentation allows the system to process items efficiently without requiring all items to be identified simultaneously, thereby improving real-time performance while maintaining identification accuracy.
2Measurement precision
If comprehensive feature comparison is performed for every item in the database, then identification accuracy can be maintained, but the computational intensity increases significantly
Solution Approach 1:
The patent applies preliminary action by capturing images of all items before performing identification operations. This allows the system to pre-process and store image data, so that during actual identification, the system only needs to compare captured images against stored reference images without performing computationally intensive feature extraction in real-time, thereby maintaining accuracy while reducing complexity.
3Measurement precision
If camera and 3D sensor positions are not recalibrated, then system operation is simpler, but accuracy in item identification and tracking deteriorates due to potential shifts in positions
Solution Approach 1:
The patent implements feedback through an automatic recalibration process that detects shifts in camera and 3D sensor positions and triggers recalibration operations. The system monitors positional changes and automatically adjusts calibration parameters to maintain tracking accuracy, eliminating the need for manual recalibration while preserving measurement precision through continuous feedback-driven adjustments.
Data Source
AI summary
A device captures an image of a first item and generates a first encoded vector for the image. The device identifies a set of items that have at least one attribute in common with the first item. The device determines the identity of the first item based at least on attributes of the first item. The device determines that a confidence score associated with the identity of the first item is less than a threshold percentage. In response, the device determines a height of the first item. The device identifies item(s) with average heights within a threshold range from the height of the first item. The device compares the first encoded vector with a second encoded vector associated with a second item from the identified item(s). If the first encoded vector corresponds to the second encoded vector, the device determines that the first item corresponds to the second item.