Multimodal Video Object Matching for Accurate Content Extraction
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Solution Overview
Problem
Existing video processing methods struggle to accurately extract relevant information from videos due to inconsistencies and errors when processing multi-modal data, leading to incomplete or inaccurate recommendations and summaries.
Innovation Solution
A method that extracts and processes multiple types of modal information (speech, image, and subtitle) from videos, using techniques like speech recognition, object detection, and natural language processing to generate accurate text information, which is then matched with preset object information to determine a comprehensive list of objects within the video.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple types of modal information are extracted and processed from videos, then the accuracy of identifying objects in videos is improved, but the device complexity and processing difficulty increase
Solution Approach 1:
The patent segments the complex multi-modal processing task into distinct modules: speech recognition module for audio processing, object detection module for visual processing, and subtitle processing module for text extraction. Each module independently processes its specific modal type and outputs structured results that are then integrated, thereby managing complexity while maintaining high accuracy in object identification.
2Measurement precision
If multiple types of modal information are extracted and processed from videos, then the accuracy of identifying objects in videos is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary processing on each modal type independently before integration: speech recognition is performed on audio segments, object detection is performed on video frames, and subtitle text is extracted and cleaned in advance. These pre-processed results are then merged and matched, which reduces the computational burden during the final integration phase and optimizes overall processing time while maintaining high accuracy.
3Productivity
If existing video processing methods are used, then the processing speed is maintained, but the accuracy and completeness of extracted information deteriorate due to inconsistencies and errors
Solution Approach 1:
The patent implements feedback mechanisms where the results from different modal processing modules are cross-validated. For example, object detection results are matched with speech recognition results and subtitle information to verify accuracy. Inconsistencies trigger re-processing or adjustment of results, ensuring high accuracy and completeness of extracted information while maintaining efficient processing through optimized feedback loops.
Data Source
AI summary
A video processing method and apparatus is provided. The video processing method includes: extracting at least two types of modal information from a received target video; extracting text information from the at least two types of modal information based on extraction manners corresponding to the at least two types of modal information; and performing matching between preset object information of a target object and the text information to determine an object list corresponding to the target object included in the target video.