Video Data Analysis Pipeline for Film Attribute Extraction
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Solution Overview
Problem
Current methods lack an efficient pipeline to uniformly extract and align video attributes from film and television dramas, limiting their utility in downstream video production and analysis.
Innovation Solution
A method and apparatus for video data analysis that involves gathering and processing input movies by removing video borders, splitting them into short clips, extracting frame images, and assessing attributes using different models to summarize and integrate properties for unified output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video borders are removed and movies are split into short clips for analysis, then measurement precision of video attributes is improved, but device complexity increases due to multiple processing steps and models
Solution Approach 1:
The patent segments the video processing pipeline into distinct modules: border removal module, video clipping module, frame extraction module, and attribute assessment module. Each module handles a specific task with dedicated processing models, enabling precise attribute measurement while maintaining organized system complexity through functional decomposition.
Solution Approach 2:
The patent introduces intermediate processing steps including border removal as a preliminary action and frame image extraction as an intermediary between video clips and attribute assessment. These intermediary components facilitate accurate attribute measurement by preparing data in appropriate formats for each analysis stage.
2Reliability
If multiple analyzing models are used to assess video attributes, then reliability of video data analysis is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary actions by removing video borders and extracting frame images before main attribute assessment. This preliminary processing prepares the data in advance, enabling multiple analyzing models to work efficiently on pre-processed inputs, thereby reducing overall processing time while maintaining analysis reliability.
Solution Approach 2:
The patent divides video content into short clips and extracts specific frame images for analysis. This segmentation allows different analyzing models to process targeted portions rather than entire videos, enabling parallel processing and reducing time loss while maintaining comprehensive attribute assessment reliability.
3Productivity
If frame images are extracted at preset rates from input movies, then productivity of attribute assessment is improved, but measurement precision of temporal attributes decreases
Solution Approach 1:
The patent applies partial action by extracting frame images at preset rates rather than analyzing every frame. This selective sampling improves productivity by reducing the number of frames processed while still capturing sufficient temporal information for attribute assessment, balancing efficiency with acceptable precision for the application requirements.
Data Source
AI summary
Methods and apparatuses are provided for movie and television series video data analysis. The method includes: gathering and reading, by a processor, a plurality of input movies; removing a video border of each input movie; splitting the input movie into short clips, based on accuracy and efficiency requirements of different analyzing models; assessing attributes of each input movie by analyzing, with the different analyzing models, the input movie, the short clips cut from the input movie, and the frame images extracted from the input movie; and summarizing the plurality of input movies based on matching and integrating the attributes assessed for each input movie.