Object Tagging System with Hierarchical Grouping
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Solution Overview
Problem
Existing automatic detection techniques for objects in images, such as face detection, face identification, and object management, are limited in handling and managing detected faces and objects effectively, often resulting in imperfections like missed detections and false alarms, and lack efficient methods for tagging and organizing detected objects.
Innovation Solution
A system comprising an object detector, identifier, and manager that processes images to detect objects, identify them, and manage the detected objects by tagging, organizing, and displaying information, including normalization and hierarchical grouping, to improve object handling and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automatic detection techniques are used to detect objects in images, then detection capability is provided, but false alarms and missed detections occur reducing reliability
Solution Approach 1:
The system implements feedback mechanisms where detection results are continuously evaluated and used to refine detection parameters. The object manager uses detection outcomes to adjust detection sensitivity and reduce false alarms over time, creating a self-improving detection system that balances reliability and accuracy.
Solution Approach 2:
The system dynamically changes detection parameters based on image characteristics and detection context. By adjusting parameters such as detection thresholds, confidence levels, and object size ranges according to specific image conditions, the system optimizes both detection reliability and precision for different scenarios.
2Productivity
If detected objects are manually managed without automated tagging, then simplicity is maintained, but time consumption increases for organizing and searching objects
Solution Approach 1:
The object manager implements self-service automation where the system automatically tags and organizes detected objects without requiring manual intervention. The system extracts object attributes, generates appropriate tags, and structures object collections autonomously, dramatically improving management efficiency while eliminating time consumption for manual organizing tasks.
Solution Approach 2:
The system performs preliminary tagging and organization actions immediately when objects are detected, rather than requiring subsequent manual processing. By pre-organizing objects with relevant tags and metadata at the detection stage, the system eliminates future time requirements for sorting and categorizing objects.
3Ease of operation
If all detected objects are displayed without normalization, then complete information is provided, but display complexity and difficulty of identification increase
Solution Approach 1:
The object manager segments the display of detected objects by organizing them into groups based on tags, categories, or relevance. This segmentation allows users to identify and navigate through objects more easily by focusing on specific categories rather than viewing all objects simultaneously, while the system maintains complete object information in the background for reference.
Data Source
AI summary
Assigning a tag to an object is disclosed. Assigning includes displaying a set of one or more objects, wherein each object has been detected from an image, receiving an indication to tag an object in the set, and assigning a tag to the object.