Image Annotation Interface With Configurable Element Order
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for adding annotation information to image data are inefficient, requiring significant user operation and resulting in a substantial amount of work to generate sufficient teacher data for machine learning models.
Innovation Solution
An information processing apparatus that acquires object configuration information defining elements and their order for annotating objects in images, provides a user interface to accept user input for specifying these elements, and stores the specified information in association with the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual annotation is performed by users specifying elements on software, then annotation information can be added to image data, but the amount of work required becomes enormous due to the large amount of teacher data needed
Solution Approach 1:
The system performs preliminary actions by automatically detecting objects and pre-arranging annotation elements (such as bounding boxes, polygons, or key points) before presenting them to users. This preliminary processing reduces the manual work required while maintaining annotation quality, directly addressing the contradiction between annotation precision and productivity.
2Productivity
If automated image generation is used to create annotation information from character information, then teacher data can be generated efficiently, but the technique does not support efficient user operation for adding annotation information to images
Solution Approach 1:
The system introduces an intermediary approach that combines automated detection with user confirmation. The automated system acts as a mediator that prepares annotation candidates, which users then review and confirm. This intermediary step maintains ease of operation while improving productivity compared to fully manual annotation.
3Adaptability or versatility
If a generic user interface is provided for annotation, then it can accommodate various annotation types, but the user operation becomes more complex and time-consuming
Solution Approach 1:
The system applies local quality by providing customized user interfaces that adapt to specific annotation tasks. Instead of a single generic interface, the UI dynamically adjusts its elements and options based on the specific annotation type and context, making each interaction simpler while maintaining overall versatility across different annotation scenarios.
Data Source
AI summary
The information processing apparatus includes: a configuration information acquisition unit that acquires object configuration information including a definition of each of one or more elements added to an image in order to indicate an object included in the image and a definition of order of the element; a user interface unit that provides a user interface being set based on a definition of the element indicated by the object configuration information according to order of the element defined by the object configuration information, in order to accept an input for specifying the element with respect to the object; and a storage control unit that controls in such a way as to store information of the element specified by the input in association with the image.