AI Storyboard Vector Generation from Reference Images
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Solution Overview
Problem
Ordinary users find it difficult and inefficient to draw a storyboard script, which affects their video creation experience.
Innovation Solution
A method and system that utilize artificial intelligence to identify elements in a reference image, match them with vector elements, and set them on a canvas to generate a storyboard script, allowing for editable and personalized modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If an ordinary user manually draws a storyboard script, then the storyboard script can be created, but the process is difficult and inefficient with high energy consumption
Solution Approach 1:
The system captures a reference image (screenshot) from the video player and copies its visual content. It then automatically identifies elements in this image and generates corresponding vector graphics, eliminating the need for users to manually redraw the storyboard from scratch.
Solution Approach 2:
The manual mechanical drawing process is replaced by an automated computer vision system. The system uses image recognition algorithms to automatically identify elements in the reference image and generates vector graphics through computational processing instead of human hand-drawing.
2Manufacturing precision
If a high-quality storyboard script is drawn manually, then the quality improves, but the energy consumption and time required increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically generating the initial storyboard vector graphics from the reference image. This preliminary generation provides a high-quality base that users can then refine, significantly reducing the total time required compared to creating everything from scratch.
Solution Approach 2:
The system copies the visual structure and content from the reference image to generate the storyboard vector graphics. This copying process preserves the quality of the original video frame while automatically creating a professional-looking storyboard that would otherwise require significant manual effort.
3Manufacturing precision
If professional shooting techniques are learned to draw storyboard scripts, then the quality improves, but the learning threshold increases
Solution Approach 1:
The system performs the complex task of storyboard creation automatically without requiring user expertise. The computer vision algorithms independently identify elements, generate vector graphics, and create the storyboard structure, making the process self-sufficient and eliminating the need for users to learn professional techniques.
Solution Approach 2:
The complex manual skills required for professional storyboard drawing are replaced by automated computer vision and vector graphics generation systems. The technical complexity is transferred from the user to the machine, allowing ordinary users to achieve professional-quality results without specialized training.
Data Source
AI summary
This application provides a storyboard script generation method. The method includes obtaining a reference image used to generate a storyboard script; obtaining an element of the reference image and element vector information of the element; obtaining a vector element matching the element; and generating the storyboard script by setting the vector element on a specified canvas based on the element vector information. According to the storyboard script generation method provided in this application, the element in the reference image is identified, and the matched vector element is correspondingly set on the specified canvas, to obtain the storyboard script in a form of a vector graph. Therefore, it is more efficient and easier to produce the storyboard script, and user experience is effectively improved.