Image Clustering for Predictable Photo Navigation
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Solution Overview
Problem
Current methods for organizing and navigating images captured by multiple users result in an unpredictable and unintuitive display, as they do not account for the patterns in which images are taken, leading to a jarring user experience.
Innovation Solution
A system that uses computing devices to detect and group images into clusters based on predetermined patterns such as panoramic, translation, and orbit patterns, allowing users to navigate smoothly by selecting and switching between images within these clusters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If images are grouped into clusters based on capture patterns, then navigation predictability and user experience improve, but system complexity increases
Solution Approach 1:
The patent segments the image set into multiple clusters based on capture patterns (panoramic, translation, orbit). Each cluster represents images with similar spatial relationships, allowing the system to apply different navigation strategies to different segments. This segmentation enables predictable navigation within each cluster while managing overall system complexity through modular organization.
Solution Approach 2:
The system performs preliminary analysis to detect capture patterns and group images into clusters before navigation begins. By pre-organizing images according to their capture relationships (spatial arrangement, movement patterns), the system establishes a structured framework that enables intuitive navigation without requiring complex real-time processing during user interaction.
2Device complexity
If images are organized without considering capture patterns, then system simplicity is maintained, but display predictability and user experience deteriorate
Solution Approach 1:
The patent changes the organizational parameter from simple sequential or random ordering to pattern-based clustering. By detecting capture patterns (such as panoramic rotation, translation movement, or orbit trajectories) and using these patterns as the basis for grouping, the system transforms the organization parameter to achieve predictable display sequences that match user expectations while maintaining reasonable system complexity.
Data Source
AI summary
The technology relates to navigating imagery that is organized into clusters based on common patterns exhibited when imagery is captured. For example, a set of captured images which satisfy a predetermined pattern may be determined. The images in the set of set of captured images may be grouped into one or more clusters according to the predetermined pattern. A request to display a first cluster of the one or more clusters may be received and, in response, a first captured image from the requested first cluster may be selected. The selected first captured image may then be displayed.