Video Clip Quality Scoring Timeline for Editing Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In video editing, users face inefficiencies when manually selecting video clips from long videos, as it is labor-intensive and time-consuming to view frames to identify suitable parts.
Innovation Solution
A method that divides a target video into clips, determines a quality score for each clip based on video frame images, and displays these scores on a timeline, allowing for quick identification and comparison of clip quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a user manually views video frames to select suitable clips from a long video, then the user can identify and select video clips, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent introduces an automated video analysis system that acts as an intermediary between the raw video content and the user. This system automatically extracts video frames, analyzes them using deep learning models to generate quality scores, and presents the results on a timeline. This intermediary automation eliminates the need for users to manually view every frame, thereby reducing labor intensity and time consumption while maintaining accurate clip selection capability
Solution Approach 2:
The patent replaces the manual mechanical process of frame-by-frame video review with an automated computational system. Instead of users physically scrolling through and evaluating each frame, the system uses computer vision algorithms and deep learning models to automatically analyze video content, generate quality assessments, and mark suitable clips on the timeline, substituting human manual labor with automated image processing and machine learning inference
2Productivity
If a user manually views video frame by frame to filter suitable parts, then the user can select video clips, but the process is not efficient
Solution Approach 1:
The patent performs preliminary automated analysis of the entire video before the user begins clip selection. The system pre-extracts all necessary video frames, pre-processes them through the deep learning model to generate quality scores, and pre-marks potential clip candidates on the timeline with visual indicators. This preliminary automation prepares the editing environment in advance, allowing users to immediately begin efficient clip selection without manual frame review, thereby significantly improving productivity and reducing time loss
Solution Approach 2:
The patent substitutes the inefficient manual frame-by-frame review process with automated image processing and deep learning-based video analysis. The system automatically evaluates video content quality, generates scoring metrics, and presents structured results on the timeline, replacing slow manual inspection with fast computational analysis and thereby enhancing overall video editing productivity
Data Source
AI summary
The present disclosure relates to a video processing method and apparatus, a readable medium and an electronic device. The method includes: dividing a target video to obtain a target video clip; determining, according to video frame images contained in the target video clip, a quality score corresponding to the target video clip; displaying the quality score corresponding to the target video clip at a time position corresponding to the target video clip on a quality score display timeline, where the time position corresponding to the target video clip is a time position where the target video clip appears in the target video. Thus, it can provide a user with a visual display result about the quality score of the target video clip, and provide a reference for the user's video clip selection, which saves the time the user spends viewing the target video clip.