Video Recording Apparatus Image Clustering Retrieval
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Solution Overview
Problem
Existing video recording apparatuses rely on externally distributed keywords for content retrieval, which may not accurately match user interests, especially for non-news content, leading to incomplete or irrelevant content presentation.
Innovation Solution
A video recording apparatus with a content accumulation part, feature extraction processing part, and content retrieval part that extracts image or voice features, acquires sorted word information through clustering processing, and retrieves relevant video content based on this information, allowing users to capture images of interest for automatic content retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If externally distributed keywords are used for content retrieval, then the system can automatically search for content involving recent topics, but the retrieval accuracy deteriorates because keywords do not always match user interests, especially for non-news content
Solution Approach 1:
The patent introduces an image recognition system as an intermediary between the user and the video content database. Instead of directly using externally distributed keywords, the system captures images, recognizes objects within them, and uses these recognized objects as intermediate search terms to query the database, thereby improving retrieval accuracy while maintaining automation
Solution Approach 2:
The patent replaces the traditional keyword-based mechanical search system with an image recognition-based system. By substituting the manual keyword selection process with automated image analysis and object recognition, the system achieves both high automation and improved retrieval precision through visual content understanding
2Ease of operation
If the system relies on externally distributed keywords, then the retrieval process is simple, but the system cannot find relevant content when keywords do not represent user interests
Solution Approach 1:
The system enables self-service retrieval by automatically capturing images from the user's environment, recognizing objects within those images, and autonomously querying the database without requiring manual keyword input. This maintains operational simplicity while significantly improving content relevance through automated visual analysis
3Measurement precision
If clustering processing is applied to word information from images, then content retrieval accuracy improves, but the system complexity increases
Solution Approach 1:
The patent segments the complex retrieval task into distinct modular components: image capture module, object recognition module, clustering processing module, and database query module. Each module handles a specific aspect of the retrieval process, making the overall complex system manageable and maintainable while achieving high retrieval accuracy through coordinated operation of these segments
Data Source
AI summary
There is provided a video recording apparatus including a content accumulation part accumulating video content, a feature extraction processing part extracting an image or voice as a feature from the video content accumulated by the content accumulation part, and obtaining word information from the extracted image or the extracted voice, a word information acquisition part acquiring sorted word information obtained using clustering processing on word information identified from an image captured by a camera, and a content retrieval part retrieving relevant video content from the video content accumulated by the content accumulation part based on the sorted word information acquired by the word information acquisition part and the word information acquired by the feature extraction processing part.