Analysis Engine Selection for Video Scene Detection
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Solution Overview
Problem
Existing techniques for analyzing moving image data, such as creating highlight videos, inadequately identify important scenes and set appropriate clipping ranges, failing to accurately detect scene start and end times and types.
Innovation Solution
An information processing apparatus that selects and utilizes multiple analysis engines for scene detection, extraction, and detailed analysis based on scene-related information, generating metadata for input videos by deciding analysis engines for scene detection, extraction, and detail description processes, and managing scene-related information for accurate scene identification and metadata generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single analysis engine is used for scene detection, then the system is simple to operate, but the scene detection accuracy and clipping range precision are insufficient
Solution Approach 1:
The patent divides the scene detection task into multiple specialized analysis engines, each responsible for specific aspects such as scene detection, clipping range determination, and scene type identification. This segmentation allows each engine to focus on specific functions, improving overall detection accuracy while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The control unit serves as a universal coordinator that manages multiple analysis engines, selecting and coordinating them based on the specific detection task requirements. This multi-functional control unit can adapt to different scene types and detection needs, improving measurement precision while keeping the system structure organized and manageable.
2Measurement precision
If multiple analysis engines are used for scene detection and clipping range identification, then the analysis accuracy improves, but the device complexity increases
Solution Approach 1:
The patent segments the complex scene analysis task into distinct functional modules handled by different analysis engines. One engine specializes in scene detection, another in clipping range identification, and a third in scene type determination. This segmentation improves clipping range precision by allowing each engine to optimize for its specific function while the control unit coordinates them efficiently.
Solution Approach 2:
Each analysis engine is designed with specialized capabilities tailored to its specific function. The scene detection engine focuses on identifying scene boundaries, the clipping range engine optimizes for precise start and end time determination, and the scene type engine specializes in categorization. This local quality optimization improves overall measurement precision without requiring all engines to be universally competent in all tasks.
3Measurement precision
If analysis engines are selected based on scene type information, then the analysis accuracy for specific scene types improves, but the processing time increases
Solution Approach 1:
The control unit performs preliminary selection of appropriate analysis engines based on the detected scene type before executing the main analysis task. By pre-selecting the most suitable engine for the specific scene type (e.g., sports scene, news scene, entertainment scene), the system achieves higher analysis accuracy for that scene type while minimizing processing time by avoiding unnecessary engine executions.
Solution Approach 2:
The system dynamically selects and switches between different analysis engines based on the scene type being processed. This dynamic adaptation allows the system to optimize processing efficiency by using the most appropriate engine for each scene type, improving measurement precision for specific scenarios while keeping overall processing time minimal through intelligent engine selection rather than running all engines sequentially.
Data Source
AI summary
An information processing apparatus includes a control unit that performs first control processing of deciding an analysis engine for scene detection from among a plurality of analysis engines on the basis of scene detection information for scene detection with respect to an input video, and second control processing of deciding an analysis engine for obtaining second result information related to the scene from among a plurality of analysis engines, on the basis of scene-related information regarding a scene obtained as first result information by the analysis engine decided in the first control processing.