Video Data Processing for Ordered Commentary Episode Albums
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Solution Overview
Problem
Existing video editing by non-professionals often lacks a fixed editing direction, leading to incomplete or inaccurate video information presentation, which complicates the presentation of viewing order in search results for movie and television commentary videos, requiring users to manually sort through multiple videos to find relevant content.
Innovation Solution
A method involving feature extraction to obtain video attribute information, including work and episode attributes, followed by classification and sorting of videos based on these attributes to generate ordered album sets, ensuring continuous and complete episode sequences for accurate presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If movie and television commentary videos are queried and displayed in a query result display box, then users can access relevant videos, but the videos are mixed together without clear viewing order, making it difficult for users to navigate and determine which videos to watch
Solution Approach 1:
The patent segments the mixed commentary videos into distinct groups based on their source label information (e.g., different movie or TV show IPs). Each group is then sorted internally according to episode attribute information, creating organized video albums rather than a single mixed list. This segmentation resolves the contradiction by maintaining all videos accessible while restoring their hierarchical viewing structure.
Solution Approach 2:
The patent performs preliminary classification and sorting operations on the commentary videos before displaying them in the query results. By pre-organizing videos into albums with proper episode sequences using feature extraction and attribute comparison, the system eliminates the need for users to manually sort through mixed videos, thereby improving ease of operation while preserving viewing order information.
2Ease of manufacture
If editing bloggers perform video editing without fixed editing direction, then video editing becomes simple and accessible, but video information such as titles and episode numbers may be incomplete or inaccurate
Solution Approach 1:
The patent implements a self-service mechanism where the system automatically performs feature extraction on commentary videos to obtain work attribute information (titles, episode numbers) and source label information. This automated information extraction compensates for the lack of professional editing direction while maintaining editing accessibility, as the system independently identifies and organizes video metadata without requiring manual intervention for accuracy.
Solution Approach 2:
The patent uses feedback mechanisms by comparing episode attribute information across multiple videos to verify completeness and accuracy. The system cross-references episode sequences within each source label group, automatically detecting and correcting information gaps or inconsistencies, thereby improving manufacturing precision while preserving the simplicity of the editing process.
3Productivity
If commentary videos are presented without structured organization, then the presentation process is simple, but users cannot efficiently navigate through videos in a series
Solution Approach 1:
The patent segments commentary videos into organized albums based on source label information, with each album containing videos from a single movie or TV show IP. Within each album, videos are further segmented by episode sequence. This segmentation structure dramatically improves user navigation efficiency while adding only moderate organizational complexity through automated classification rules.
Solution Approach 2:
The patent implements a universal organization structure that handles multiple types of video content (different IPs, different episode formats) through a single classification framework based on source labels and episode attributes. This multi-functional approach improves presentation efficiency across diverse video types without requiring separate complex organization systems for each content type.
Data Source
AI summary
A video data processing method includes obtaining candidate video(s), performing feature extraction on each candidate video to obtain video attribute information corresponding thereto and including work and episode attribute information, obtaining source label information corresponding to each candidate video, classifying the candidate video(s) according to the source label information to obtain an initial video set containing candidate video(s) having same source label information, determining candidate video(s) that have target work attribute information as target video(s), sorting the target video(s) according to episode attribute information corresponding to the target video(s) to obtain sorted video(s), and, if the episode attribute information corresponding thereto satisfies episode legitimacy condition, determining the sorted video(s) as ordered album video(s) and generating a video album set containing the ordered album video(s).