Automated Video Storyboard Generation via Narrative Unit Segmentation
Solution Overview
Problem
Existing methods for creating storyboards and comic strips from videos are cumbersome and time-consuming, requiring manual intervention, and lack automated solutions for generating these from existing video content.
Innovation Solution
An automated system and method that extracts audio and visual frames from videos to identify key frames based on exposition, conflict, and resolution units, manipulating them to generate comic strips or storyboards with optional user intervention for format and content adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual methods are used to create storyboards and comic strips from videos, then the quality and control of the output can be maintained, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The video processing system segments the video content into three basic narrative units (exposition, conflict, resolution) and extracts key frames from each unit. This segmentation allows automated generation of comic strips by processing distinct narrative components separately, improving productivity while managing complexity through modular processing of video segments.
Solution Approach 2:
The system creates visual copies of video content by extracting and manipulating key frames to generate comic strip panels. Instead of manual redrawing, the system automatically copies and transforms video frames into comic-style visuals, significantly increasing generation speed while reducing the need for complex manual intervention.
2Loss of time
If automated systems are implemented to generate comic strips from videos, then productivity increases, but the system complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-identifying the three basic narrative units (exposition, conflict, resolution) and pre-extracting key frames from video content before generating the final comic strip. This preliminary processing reduces the time required for final assembly and reduces complexity by preparing components in advance for efficient automated composition.
Solution Approach 2:
The automated system performs self-service by independently extracting audio and visual frames, identifying narrative units, selecting key frames, and assembling comic strips without continuous manual intervention. This self-automated process reduces turnaround time while managing complexity through integrated processing that handles multiple tasks autonomously.
3Measurement precision
If key frames are extracted based on both audio and visual frames, then the accuracy of narrative identification improves, but the processing complexity increases
Solution Approach 1:
The system merges audio frame analysis and visual frame analysis to identify the three basic narrative units (exposition, conflict, resolution). By combining both audio and visual information, the system achieves more accurate narrative identification while managing processing complexity through integrated multi-modal analysis that leverages complementary information from both sources.
Data Source
AI summary
A method, a system, and a computer program product code for generating a series of still images from an input video file are provided. The series of still images may include, but are not limited to, a comic strip and a storyboard. The method includes extracting audio and visual frames from the video file. Thereafter, basic units of the video file are identified. The basic units are exposition (beginning), conflict (middle), and resolution (end). Thereafter, key frames are extracted from the basic units based on at least one of audio frames, visual frames, and a combination of the visual frames and the audio frames. Then, the extracted key frames are manipulated to output a series of still images. Subsequently, narration in the form of audio or text is attached to the still images to generate at least one of comic strips and storyboards.