Video Description Generation Using Global POS Sequence Features
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Solution Overview
Problem
Conventional video description methods generate simplistic natural language descriptions that do not conform to human language habits, as they directly convert frame-level features to video-level features without adequate semantic alignment, leading to inadequate understanding and analysis.
Innovation Solution
A method that generates video description information by obtaining a video feature sequence on a frame level, generating a global part-of-speech sequence feature, and using this feature to produce accurate natural language descriptions through a combination of convolutional and recurrent neural networks, along with attention mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If video data is processed and stored in a database before being sent to a terminal, then the terminal can access video information, but the processing time and system complexity increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-processing video data into structured formats (extracting video ID, title, description, tags, and cover image) and storing them in a database before terminal access. This allows the terminal to quickly retrieve pre-processed information without performing complex processing in real-time, thus reducing terminal processing time while ensuring complete video information delivery.
2Loss of information
If comprehensive video data processing is performed including extraction, storage, and retrieval operations, then video information completeness is improved, but system complexity and processing duration increase
Solution Approach 1:
The patent applies segmentation by dividing the video processing system into distinct functional modules: a video processing unit that extracts and structures video data, a database storage unit that organizes and stores the processed data, and a terminal retrieval unit that accesses specific video information. This modular segmentation reduces overall system complexity by allowing each component to handle specific tasks independently while maintaining complete video information delivery.
Data Source
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AI summary
A video description information generation method, a video processing method, and corresponding devices. The video description information generation method comprises: obtaining a frame-level video feature sequence corresponding to a video to be described (S101); generating a global part of speech sequence feature of said video according to the video feature sequence (S102); and generating natural language description information of said video according to the global part of speech sequence feature and the video feature sequence (S103).