Image Grouping via Object Detection and Remote Processing
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Solution Overview
Problem
Current image viewing applications on mobile devices require complex facial recognition and manual operations to group images by objects, making it difficult to share specific images with others efficiently.
Innovation Solution
A network-based system that organizes images into groups based on common objects, time, and location, allowing users to select objects in an image, identify their characteristics, and automatically gather similar images from local or remote storage for easy sharing and grouping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If facial recognition applications are used to group images by objects, then image grouping capability is improved, but device complexity and operational difficulty increase
Solution Approach 1:
The patent introduces an intermediary service server that handles the complex facial recognition and image grouping operations remotely. The mobile device itself does not need to contain complex grouping algorithms - instead, it communicates with a server that performs the heavy lifting of analyzing images, identifying objects, and organizing them into groups. This resolves the contradiction by moving complexity from the device to an external service.
Solution Approach 2:
The service server provides universal image grouping functionality that can handle multiple objects, people, and scenarios through a single interface. Rather than requiring separate applications for different grouping needs, the system offers a unified service that automatically groups images by any detectable object or person, simplifying the user experience while maintaining versatility.
2Ease of operation
If manual operations are used to group images into collections, then ease of operation is improved, but time consumption increases
Solution Approach 1:
The system enables self-service image grouping where the service server automatically performs image analysis, object detection, and group creation without requiring manual user intervention. Users simply provide access to their image collections, and the system autonomously organizes them into groups based on detected objects, people, and contextual information, eliminating time-consuming manual operations.
Solution Approach 2:
The service server performs preliminary analysis of images to pre-organize them into groups before users need to access them. By proactively processing and categorizing images in advance, the system makes grouped images readily available when users want to view or share them, saving significant time compared to on-demand manual grouping.
3Productivity
If images are grouped by objects, then image organization is improved, but ease of sharing with specific individuals deteriorates
Solution Approach 1:
The system incorporates feedback mechanisms where users can review automatically created image groups and provide input on sharing preferences. The service server learns from user interactions and automatically adjusts sharing settings based on the objects or people in each group, making the sharing process as easy as the organization process while maintaining high productivity.
Data Source
AI summary
Techniques for grouping images are disclosed. In some situations, the techniques include identifying at least one event-based image group among a plurality of images based on an event that is associated with each identified image, receiving a selection of one or more objects in a first image of the identified event-based image group, identifying other images in the identified event-based image group that each include at least one of the selected one or more objects, and associating the identified images with the first image. In one instance, the selected objects include individuals captured in the image.