Semantic Region Detection for Dynamic Image Panning and Zooming
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Solution Overview
Problem
Conventional slide shows of still images are dull and lack animation, failing to effectively simulate the dynamic nature of video, which limits their engagement and multimedia appeal.
Innovation Solution
A method for generating a slide show by performing semantic or non-semantic analysis to detect regions of interest, such as human faces or symmetric patterns, and then zooming and panning the image between selected regions to create a dynamic display that mimics video footage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional slide show displays are used to present still images, then the presentation is simple and easy to implement, but the display is dull and lacks animation
Solution Approach 1:
The patent applies dynamics by transforming static image display into dynamic presentation through automated panning and zooming operations. The system dynamically adjusts the display region and magnification level based on detected semantic regions, creating animated effects that simulate video footage while maintaining automated operation.
Solution Approach 2:
The system employs self-service through automatic semantic region detection and automated slide show generation. The computer automatically identifies important regions in images, determines optimal panning and zooming parameters, and generates the animated slide show without requiring manual user configuration, thus maintaining ease of operation while enhancing engagement.
2Productivity
If video effects are simulated in slide show, then the multimedia appeal and engagement are improved, but the processing complexity increases
Solution Approach 1:
The patent applies preliminary action by performing semantic region detection and analysis before generating the slide show. The system pre-identifies important regions, pre-calculates panning paths, and pre-determines zooming parameters, which simplifies the subsequent slide show generation process and manages processing complexity effectively.
Solution Approach 2:
The system uses semantic region detection as an intermediary step between the input images and the final slide show output. This intermediary process automatically identifies key regions and generates control parameters for panning and zooming, bridging the gap between simple image input and complex video-like output without requiring direct complex processing.
3Measurement precision
If all pixels of high-resolution CCD images are used for display, then the picture quality is improved, but the processing speed decreases
Solution Approach 1:
The patent applies taking out by extracting and focusing only on semantically important regions rather than processing the entire high-resolution image. The system identifies and extracts key regions containing important content, then performs panning and zooming operations only on these extracted regions, reducing processing load while maintaining picture quality in the displayed areas.
Solution Approach 2:
The system applies local quality by applying different processing levels to different regions of the image. High-resolution processing is applied only to semantically important regions that require detailed display, while other regions receive less intensive processing. This selective approach maintains picture quality where needed while improving overall processing speed.
Data Source
AI summary
The present invention discloses methods for generating a slide show of an image. With the methods, every still image could be displayed with the vivid effect of a dynamic video. The steps of one method according to the present invention comprise: performing a semantic analysis of a image for detecting semantic regions; selecting a first region and a second region from the semantic regions; determining a first and a second zooming levels of the first and second regions, respectively; and generating a slide show of the image by panning the image from the first region to the second region while zooming the image from the first zooming level to the second zooming level, gradually.