Visual Search Timeline Indexing via Key Frame Extraction
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Solution Overview
Problem
Conventional computing devices rely on text-based search methods for media content retrieval, which can be inefficient, especially when users need to recall visual media events, as they do not effectively utilize visual data for search and recall processes.
Innovation Solution
A visual search system that generates a searchable visual history timeline by capturing and processing image data from device displays, using a decay function to filter and sort data, and presenting key frames associated with user activities across multiple applications, leveraging Bayesian belief networks to predict image access patterns and reduce redundant information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If text-based search methods are used for media content retrieval, then the search process is simple to implement, but the search efficiency and user recall capability are insufficient
Solution Approach 1:
The patent replaces text-based search mechanisms with visual search mechanisms. Instead of relying on textual metadata or file names, the system captures display images, extracts visual features, and performs image-based similarity search. This substitution enables users to search for media content by visual appearance, significantly improving search efficiency and recall capability while maintaining manageable system complexity through the use of established image processing techniques.
2Loss of information
If all image data from device displays is stored for visual search, then the completeness of visual history is improved, but the data storage requirement and processing load increase significantly
Solution Approach 1:
The patent extracts only the essential visual information needed for search functionality. Instead of storing complete image sequences or raw display data, the system captures key frames, extracts dominant visual features, and stores compressed feature representations. This extraction approach preserves the essential visual history information required for effective search while dramatically reducing the storage burden and processing requirements.
Solution Approach 2:
The patent inverts the traditional approach by not storing images and then searching, but rather storing extracted visual features and performing search operations on the feature space. This inversion reduces data volume while maintaining search effectiveness, as feature representations are much more compact than full images yet retain the essential information needed for visual similarity search.
3Ease of operation
If visual search functionality is added to computing devices, then the user recall capability is enhanced, but the device complexity and processing requirements increase
Solution Approach 1:
The patent introduces visual feature extraction and matching as an intermediary process between user input and media retrieval. The system captures display images, extracts visual features, builds an index of media content based on these features, and uses the intermediary feature-matching process to enable efficient visual search. This intermediary layer enhances user recall capability by allowing visual-based queries while managing complexity through modular architecture and optimized feature processing.
Data Source
AI summary
In various example embodiments, a system and method for visual search and associated data decay models are presented. In one example embodiment, image history data associated with an output display of the machine is captured. The image history data is analyzed to identify groups of images associated with a plurality of events, and context information is identified that is associated with the plurality of events. One or more images for each event of the plurality of events is selected as a key image for an associated event as part of a plurality of key images, and a searchable event timeline index is generated. Key frames from an index of activities of one or more devices may then be displayed as part of a user search for information.