Video Scene Classification Using Feature Extraction
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Solution Overview
Problem
Existing video processing technologies fail to effectively isolate and classify explaining and explained scenes within a video, which are crucial for operation procedures and other types of videos, leading to difficulties in categorizing and retrieving specific content.
Innovation Solution
An information processing apparatus is developed, comprising a feature extraction unit, a discriminating unit, and a categorization unit, which analyzes video content to extract feature elements such as hand movement patterns, speech rates, and screen changes to differentiate between explaining and operation scenes, allowing for accurate classification and categorization of video segments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing video processing technologies are used, then general video analysis is possible, but isolation and classification of explaining and explained scenes cannot be effectively performed
Solution Approach 1:
The patent segments video content into distinct explaining scenes and explained scenes by analyzing feature elements. The discriminating unit divides the video stream into separate categories based on extracted features, enabling precise isolation of different scene types that existing technologies cannot distinguish.
Solution Approach 2:
The patent changes the parameter of scene classification by introducing multiple feature elements (hand movement patterns, speech rates, screen changes) rather than using single-parameter analysis. This multi-parameter approach enables accurate discrimination between explaining and explained scenes, resolving the limitation of existing technologies.
2Measurement precision
If video content is analyzed without feature element extraction, then processing is simpler, but accurate discrimination between explaining and operation scenes cannot be achieved
Solution Approach 1:
The patent applies preliminary action by extracting feature elements from video content before performing scene discrimination. The feature extraction unit prepares the data in advance by identifying hand movement patterns, speech rates, and screen changes, which then facilitates accurate scene classification without requiring complex real-time analysis during discrimination.
Solution Approach 2:
The patent introduces feature elements as an intermediary between raw video content and scene classification. These extracted features serve as intermediate representations that simplify the discrimination task, acting as a mediator that transforms complex video data into discriminable patterns for the discriminating unit.
3Productivity
If explaining and explained scenes are not classified, then video processing is faster, but retrieval and categorization of specific content becomes difficult
Solution Approach 1:
The patent extracts classification information by separating explaining and explained scenes into distinct categories. The categorizing unit extracts and organizes scene types, creating structured metadata that enables efficient retrieval without slowing down the core video processing operations. This extraction of organizational information prevents loss of categorization data while maintaining processing efficiency.
Data Source
AI summary
An information processing apparatus includes a feature extraction unit that analyzes a video to extract a feature element, a discriminating unit that, based on a difference in the feature element for each of multiple portions of the video, performs discrimination that discriminates between an explaining scene and an explained scene, the explaining scene being a scene providing explanation, the explained scene being a captured scene of what is explained in the explaining scene, and a categorizing unit that categorizes each portion of the video based on a result of the discrimination.