Distributed Camera Object Identification by Physical Uniqueness
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Solution Overview
Problem
Existing object identification and tracking techniques that rely on barcodes, QR codes, or RFID tags are prone to failure if these identifiers become detached, damaged, or obscured, incurring financial and personnel costs, and require substantial investment in hardware and software for creating unique identifiers.
Innovation Solution
Object uniqueness measurement techniques that utilize distributed cameras to measure and quantify the physical characteristics of objects, automatically generating identifiers based on these properties, allowing for dynamic tracking and mapping to traditional identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional identifiers (barcodes, RFID tags) are attached to objects for identification and tracking, then object identification capability is provided, but reliability deteriorates when identifiers become detached, damaged, or obscured
Solution Approach 1:
The patent extracts the identification function from physical attachments (barcodes, RFID tags) and embeds it directly into the object's visual appearance through painted patterns. This eliminates the need for separate identifier components that can detach or damage, making the identification intrinsic to the object itself.
Solution Approach 2:
The patent creates visual copies of identification information by painting distinctive patterns directly on objects. These painted patterns serve as permanent visual replicas of object identities that can be captured by cameras and processed for tracking, replacing fragile physical tags with durable visual representations.
2Productivity
If manual and automatic scanning of identifiers is performed to track objects, then object tracking capability is achieved, but loss of time increases due to scanning operations
Solution Approach 1:
The patent replaces mechanical scanning systems (barcode scanners, RFID readers) with optical capture using cameras. The identification patterns are captured as images and processed through computer vision algorithms, eliminating the need for physical scanning operations and reducing tracking time.
Solution Approach 2:
The patent pre-applies distinctive painted identification patterns to objects during manufacturing or before deployment. This preliminary marking ensures that objects are immediately trackable upon entering the system without requiring on-the-spot identifier attachment or scanning setup, reducing initial tracking delays.
3Reliability
If unique identifiers are created and assigned to each object, then object distinction capability is improved, but loss of substance increases due to materials used for identifiers and labels
Solution Approach 1:
The patent merges the identification function with the object's surface by painting patterns directly onto it. This integration eliminates the need for separate identifier materials (stickers, tags, labels) and uses the object's own surface as the carrier for identification information, reducing material consumption.
Solution Approach 2:
The patent uses paint as a disposable, easily applied material that can be directly deposited on objects without requiring durable, expensive identifier components. The painted patterns serve their identification purpose effectively and can be reapplied if needed, reducing overall material costs and waste.
Data Source
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AI summary
Example apparatus disclosed herein are to generate first descriptive data of a first physical characteristic of a first object based on first camera sensor data from a first camera sensor, and generate second descriptive data of a second physical characteristic of a second object based on second camera sensor data from a second camera sensor different from the first camera sensor. Disclosed example apparatus are also identify, based on the first descriptive data and the second descriptive data, common physical characteristics associated with both the first object and the second object, first unique physical characteristics associated with the first object, and second unique physical characteristics associated with the second object. Disclosed example apparatus are further to identify the first object and the second object as one of a same object or different objects based on the common physical characteristics, the first unique physical characteristics, and the second unique physical characteristics.