Dynamic Thumbnail Selection for Video Search Results
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Solution Overview
Problem
Existing image processing systems struggle to provide representative thumbnails for video search results, leading to difficulties in interpreting search results due to poorly selected images, such as subjects facing away from the camera or being obscured.
Innovation Solution
A method and system for computing similarity scores for images in search results based on a search query, selecting a representative image through modification steps like expanding, cropping, rotating, and color-correcting, and presenting these images in a search result listing, ensuring the representative image accurately reflects the content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a thumbnail is automatically selected from search result images, then the system complexity is reduced, but the representativeness and interpretability of the thumbnail deteriorates
Solution Approach 1:
The system computes a representativeness score for each candidate thumbnail and uses this feedback metric to select the optimal thumbnail. This quantitative feedback mechanism ensures that the automatically selected thumbnail accurately represents the video content without requiring manual intervention, thus resolving the contradiction between system simplicity and thumbnail quality.
Solution Approach 2:
The patent replaces manual thumbnail selection (mechanical/human system) with an automated computational system that calculates representativeness scores based on image analysis. This substitution maintains system simplicity while improving thumbnail representativeness through algorithmic evaluation of multiple candidate images.
2Loss of information
If multiple modification steps are performed on images to improve thumbnail quality, then the thumbnail representativeness improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs image modifications such as cropping, resizing, and color correction as preliminary steps before computing the representativeness score. By preparing multiple modified versions of candidate images in advance, the system can quickly evaluate their representativeness and select the best thumbnail without time-consuming processing during the selection phase.
Solution Approach 2:
The patent dynamically adjusts the extent of image modifications based on the characteristics of each candidate image and the requirements of the search context. Rather than applying fixed, time-consuming modifications to all images, the system adapts the processing level to achieve optimal thumbnail quality efficiently.
3Measurement precision
If the system computes similarity scores for multiple images in each search result, then the accuracy of thumbnail selection improves, but the computational complexity increases
Solution Approach 1:
The patent segments the thumbnail selection process into distinct stages: first filtering candidate images from video frames, then computing representativeness scores only for these filtered candidates. This segmentation reduces the number of images requiring complex similarity computations, thereby lowering overall computational complexity while maintaining selection accuracy.
Solution Approach 2:
The system changes the parameters used for image evaluation by computing representativeness scores based on multiple factors including visual content analysis, relevance to search query, and quality metrics. This multi-parameter approach improves selection accuracy while the scores are computed efficiently using optimized algorithms that balance precision with computational resources.
Data Source
AI summary
The present disclosure is drawn to methods and systems for providing a representative image for a search result in a search result listing of a searching system. At least one search result based on a search query is received. Each search result has a plurality of images. For each search result, a similarity score for at least some of the images is computed, based on a similarity with the search query. Then, at least one of the images is selected, on the basis of the similarity score, and the selected image is assigned as the representative image of the search result. A number of modification steps may be performed on the search result prior to computing the similarity score. The search result and assigned representative image may also be presented in a search result listing.