Sample-Scene Recognition Rules for Accurate Content Scene Cutting
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Solution Overview
Problem
Existing systems require cumbersome and often inappropriate user settings for recognition engines to accurately cut desired scenes, leading to difficulties in accurately detecting metadata for scene cutting.
Innovation Solution
An information processing apparatus and method that includes a setting unit for recognition units and a generation unit for cutting rules, which are set based on user-designated sample scenes, allowing for accurate detection and cutting of scenes by performing recognition processing on the content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the recognition engine is set by the user for every category of content, then the detection accuracy of metadata may be improved, but the operation complexity and time consumption increase significantly
Solution Approach 1:
The system performs self-service by automatically acquiring recognition parameters and setting the recognition engine based on the input content, without requiring manual user configuration. The control device extracts metadata from the content, selects appropriate recognition parameters based on the content type, and configures the recognition engine automatically, thereby resolving the contradiction between detection accuracy and operation complexity.
2Measurement precision
If the recognition engine is set by the user for every category of content, then the detection accuracy of metadata may be improved, but the time consumption for setup increases
Solution Approach 1:
The system performs preliminary action by pre-acquiring recognition parameters from the content itself and pre-configuring the recognition engine before actual metadata detection begins. The control device analyzes the content type, selects appropriate parameters in advance, and sets up the recognition engine proactively, eliminating the need for time-consuming manual configuration and enabling immediate detection operations.
3Adaptability or versatility
If manual setting of recognition engine is required, then flexibility in detection parameters may be improved, but the ease of use deteriorates
Solution Approach 1:
The system dynamically changes parameters by automatically adjusting recognition parameters based on the analyzed content characteristics. The control device extracts metadata from the content, determines the content type, and selects appropriate recognition parameters accordingly, enabling the system to adapt to different content categories automatically without requiring manual parameter adjustment, thus maintaining both flexibility and ease of use.
Data Source
AI summary
There is provided an information processing apparatus, an information processing method, and a program capable of accurately cutting a desired scene desired by a user. Setting of a recognition unit that detects detection metadata, which is metadata regarding a predetermined recognition target, by performing recognition processing on the recognition target is performed on the basis of a sample scene, which is a scene of a content designated by a user. Then, a cutting rule for cutting scenes from the content is generated on the basis of the detection metadata detected by performing the recognition processing on the content as a processing target by the set recognition unit and the sample scene. The present technology can be applied to, for example, an information processing system that cuts a desired scene from a content.