Object Grouping and Tagging for Image Detection Management
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Solution Overview
Problem
Existing automatic detection techniques for objects in images, such as face detection, are limited in managing detected faces and objects, with issues like imperfect detection, false alarms, and inadequate handling of object identification and tagging.
Innovation Solution
A system and process for detecting, processing, and managing objects in images, including automatic and manual detection, object identification, tagging, normalization, and display, using a system comprising an object detector, identifier, and manager, which handles objects with improved tagging, grouping, and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automatic detection techniques are used to detect objects in images, then detection speed and automation are improved, but detection accuracy and reliability deteriorate due to false alarms and imperfect detection
Solution Approach 1:
The system implements feedback mechanisms where detected objects are reviewed, tagged, and verified. The object manager provides feedback loops that allow correction of false detections and improvement of detection algorithms based on tagged data, thereby maintaining automation while improving reliability.
Solution Approach 2:
The patent introduces an intermediary tagging system between automatic detection and final object identification. Tags serve as intermediaries that bridge automated detection results with human verification, allowing the system to maintain high automation while improving detection accuracy through structured intermediate processing.
2Ease of operation
If multiple detected objects are managed without grouping, then individual object processing is simplified, but object identification and location efficiency deteriorate
Solution Approach 1:
The system segments detected objects into groups based on shared tags and characteristics. The object manager divides the large set of detected objects into manageable groups, allowing operators to process objects in organized segments rather than individually, thus improving identification efficiency without complicating individual object processing.
Solution Approach 2:
The patent adds a grouping dimension to object management by organizing objects into hierarchical groups based on tags. This creates an additional organizational layer that enables efficient navigation and location of objects without affecting the simplicity of processing individual objects within each group.
3Measurement precision
If detailed tagging and grouping information is displayed for all objects, then object identification efficiency is improved, but display complexity and information overload increase
Solution Approach 1:
The system applies local quality by displaying different levels of detail for different objects based on their relevance and grouping. The object manager selectively displays tag information and grouping details only where necessary, providing comprehensive identification information for selected objects while keeping the overall display clean and manageable.
Solution Approach 2:
The display system is made dynamic, allowing users to interactively explore object details. The object manager enables dynamic expansion and collapse of group information, so that detailed tagging and grouping information is displayed on-demand rather than all at once, maintaining identification precision while reducing display complexity.
Data Source
AI summary
Displaying an object is disclosed. Displaying includes obtaining a first group of objects associated with a first tag and a second group of objects associated with a second tag, wherein at least one object in the first group or the second group has been detected from an image; and displaying the first group and the second group, wherein the objects are arranged to indicate to which group they belong.