Image Generation Method for Video Effect Objects
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Solution Overview
Problem
Existing image generation technologies for video applications are limited by the lack of diversity and quality in effect objects, leading to single and unimpressive display effects, which negatively impact user experience.
Innovation Solution
An image generation method that determines a reference trunk direction and extension information based on initial points, target offsets, and parameters to randomly generate effect images, such as snowflakes or branches, enhancing pattern diversity and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If random generation parameters are introduced to improve pattern diversity, then the display effect quality is improved, but the generation complexity increases
Solution Approach 1:
The patent applies parameter changes by introducing multiple random generation parameters (target offset, reference trunk direction, extension position, target extension direction) to transform the effect object generation process. These parameters modify the structural characteristics of the effect image, enabling diverse pattern generation while maintaining a systematic approach to complexity management.
Solution Approach 2:
The patent implements dynamics by making the effect object generation process adaptive and variable rather than static. The random generation parameters allow the system to dynamically adjust the structure, direction, and extension of effect objects, creating diverse patterns that adapt to different generation conditions while following consistent procedural rules.
2Manufacturing precision
If multiple generation parameters are used to enhance effect image quality, then the display effect is improved, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-establishing the generation framework and parameter relationships before actual effect image creation. The system pre-defines how target offset, reference trunk direction, and extension parameters interact, allowing rapid generation once parameters are set, thus reducing actual processing time while maintaining high quality output.
Data Source
AI summary
Embodiments of the present disclosure provide an image generation method, an apparatus, an electronic device, and a storage medium. The method comprises: determining a reference trunk direction of an effect object according to a predetermined initial point and a target offset in response to an image generation condition being satisfied; determining at least one piece of extension information according to the initial point, the reference trunk direction and a predetermined target parameter; generating an effect image of the effect object based on the at least one piece of extension information.