Avatar Generation from Composite Still Images
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Solution Overview
Problem
Conventional systems for creating animated content, such as avatars and sequences, are limited in functionality and flexibility, often requiring expensive and complex computer graphics systems that primarily focus on high-quality animation, and lack the ability to easily incorporate user-specific features from still images.
Innovation Solution
A system and method that extracts features from a composite still image to create avatars and animated sequences, using image segmentation and object recognition algorithms to identify and animate human body parts, allowing users to select and customize images, backgrounds, and motion templates, enabling the creation of personalized animated content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional computer graphics systems are used to create animated content, then high-quality animation can be achieved, but the systems become expensive and complex
Solution Approach 1:
The system segments the animation creation process into distinct modules: image segmentation to extract body parts, object recognition to identify human figures, feature extraction to obtain characteristic data, and animation synthesis to generate the final animated content. This modular approach reduces overall system complexity while maintaining high animation quality through specialized processing at each stage.
Solution Approach 2:
The patent introduces an intermediary processing pipeline that bridges still images and animated sequences. By extracting features from static images and translating them into animation parameters through intermediate representation layers, the system achieves high-quality animation without requiring complex real-time capture systems, thus reducing device complexity.
2Measurement precision
If green screen techniques and physical props are used to isolate user faces, then facial images can be captured, but the functionality and flexibility are very limited
Solution Approach 1:
The system employs a universal image processing framework that can handle diverse input images (portraits, group photos, artistic compositions) and generate multiple types of animated content (talking avatars, action sequences, expressive animations). This multi-functional approach eliminates the need for specialized green screen equipment while providing flexible functionality across different scenarios.
Solution Approach 2:
Instead of requiring physical presence and green screen techniques, the system creates virtual copies of users from static images. By extracting and animating key features from copied image data, the system achieves facial image capture accuracy without the functional limitations of physical capture systems, enabling versatile applications.
3Productivity
If automated systems are used to create animated sequences, then production time is reduced, but the ability to incorporate user-specific features from still images is limited
Solution Approach 1:
The system performs preliminary feature extraction from still images before animation generation. By pre-processing images to identify and extract characteristic features (facial structures, body poses, distinctive markings), the system preserves user-specific accuracy while maintaining automated production speed. This preliminary action ensures that automated processes do not sacrifice feature accuracy.
Data Source
AI summary
A user may create an avatar and/or animated sequence illustrating a particular object or living being performing a certain activity, using images of portions of the object or living being extracted from a still image or set of still images of the object or living being.