Image Clustering and Ordering for Video Coherence
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current image viewing and selection technologies are inefficient for large datasets, as they do not effectively cluster and order images based on visual coherence, leading to aesthetically unpleasing presentations and difficulty in selecting the best images from similar ones, especially when images are taken by different devices or users.
Innovation Solution
An image processing method that clusters images into scenes based on similarity measures and orders them within scenes for video coherence, allowing for smooth and aesthetically pleasing presentations, and can be stored and played using standard video codecs and players.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If images are sorted by timestamp from multiple devices, then chronological order is achieved, but visual coherence deteriorates causing aesthetically unpleasing presentations
Solution Approach 1:
The patent segments the image set into multiple scenes based on visual coherence criteria. Each scene contains images that are visually similar and coherent, regardless of their timestamp order. This segmentation resolves the contradiction by allowing chronological ordering within scenes while maintaining visual coherence between scenes through deliberate transitions or gaps.
2Ease of operation
If images are displayed in mosaic arrangement, then viewing efficiency is limited to small sets, but selecting from large datasets becomes inefficient
Solution Approach 1:
The patent transitions from a two-dimensional mosaic layout to a temporal dimension by ordering images sequentially in video format. This allows efficient navigation through large datasets using time-based controls (play, pause, rewind, fast-forward) while maintaining visual coherence through scene-based grouping. The temporal dimension provides scalable efficiency for large image quantities.
3Speed
If slideshow plays images sequentially, then review speed increases, but viewing time per image decreases
Solution Approach 1:
The patent implements dynamic playback speeds that adapt to scene transitions. Within coherent scenes, images can be displayed faster since they are visually similar. At scene boundaries, the playback naturally pauses or slows, allowing viewers to absorb the transition. This dynamic approach maintains high overall review speed while ensuring adequate viewing time at critical decision points.
4Stability of the object's composition
If manual ordering is used for slideshow creation, then presentation quality improves, but creation time increases
Solution Approach 1:
The patent implements automated scene detection and ordering algorithms that analyze image content, metadata, and coherence metrics to automatically create visually coherent presentations. The system serves itself by making intelligent ordering decisions without manual intervention, achieving presentation quality comparable to manual curation while dramatically reducing creation time. Users can override automated decisions if desired, but the default self-service approach resolves the time-quality tradeoff.
Data Source
AI summary
An image processing method comprises: clustering images of a set of images to generate a plurality of scenes each comprising an unordered cluster of images; ordering images within scenes respective to video coherence to generate ordered scenes comprising ordered sequences of images; and generating video content as images ordered in accordance with the ordered sequences of images comprising the scenes. In some embodiments, the video content is converted to video comprising video frames played at a predetermined frame rate.