Image Similarity Linking for Collaborative Data Sharing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current social networking sites fail to effectively link and aggregate comments across multiple instances of the same digital image, even when uploaded by different users, lacking the ability to consolidate data and maintain user control over their images.
Innovation Solution
A computer-implemented method that compares uploaded images with previously uploaded images to determine similarity, linking attendant data across similar images, allowing users to share and edit data while maintaining control over their images, using a central data repository and image recognition technology.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comment data is saved related to the unique instance of the photograph to protect user privacy, then user control over their image is maintained, but comments and data cannot be shared across multiple instances of the same photo
Solution Approach 1:
The patent segments data into two distinct layers: instance-specific data (stored with individual photo copies) and aggregate data (stored separately and shared across similar photos). This segmentation allows each photo instance to maintain its own privacy settings while enabling collaborative commenting through the separate aggregate data structure that links similar photos together.
Solution Approach 2:
The patent introduces an intermediary aggregate data structure that acts as a mediator between multiple instances of the same photo. This intermediary layer stores comments and data that are shared across similar photos, allowing users to collaborate on photos they don't own while the original owner maintains control through instance-specific data.
2Loss of information
If a centralized system aggregates all photo data to enable collaborative commenting, then comment sharing across similar images is improved, but individual users lose control over their uploaded images
Solution Approach 1:
The system segments data storage and control into instance-specific portions (maintained by individual users) and aggregate portions (shared across similar photos). This segmentation enables collaborative commenting functionality while preserving individual user control over their uploaded images through the instance-specific data layer.
Solution Approach 2:
The patent applies local quality by allowing different data layers to have different access controls and privacy settings. Instance-specific data maintains strict user control, while aggregate data enables collaborative commenting. Each layer has its own quality characteristics appropriate to its function.
3Loss of information
If image similarity comparison is performed across all uploaded images, then the ability to link similar photos is improved, but system complexity and processing time increase
Solution Approach 1:
The patent performs preliminary actions by extracting and storing key visual features from images during the upload process, rather than performing full image comparison only when needed. This preliminary feature extraction enables faster and more efficient similarity comparison later, reducing the complexity of real-time processing.
Solution Approach 2:
The system creates simplified copies of image data in the form of feature vectors or metadata representations that can be compared efficiently. Instead of comparing entire high-resolution images, the system works with these compressed representations, reducing processing complexity while maintaining the ability to identify similar photos.
Data Source
AI summary
There are provided methods and systems for linking data related to a set of similar images in a manner that both facilitates collaborative data sharing and commenting to generate a more robust set of information about the collective set of images while concurrently allowing users to maintain control over their particular images. A useful and collaborative development of content is achieved between many users interacting with similar versions of the same image. The interacting users may, for example, be friends who may have shared the image through other means, perhaps many years before, or may otherwise be unknown to one another.