Dynamic Avatar-Head Cage Generation for Efficient Mesh Alignment
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Solution Overview
Problem
Existing methods for creating avatar heads in virtual experiences are manual and labor-intensive, requiring significant time and computational resources for caging processes to align hairstyles and clothing accurately with the underlying mesh topology.
Innovation Solution
A method for automatically generating a cage based on the mesh of an avatar head using landmark-prediction or UV-regression models, aligning the initial cage with the mesh to fit the avatar head, thereby reducing time and computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual caging processes are used to align hairstyles and clothing with avatar mesh topology, then alignment accuracy is improved, but time consumption and computational resources increase significantly
Solution Approach 1:
The system performs preliminary actions by pre-computing correspondence between template cage vertices and avatar mesh vertices before the actual caging process. This includes identifying matching vertices, computing transformation matrices, and establishing geometric relationships in advance, so that when hairstyles and clothing need to be aligned, the framework is already prepared and can quickly apply pre-established correspondences without manual intervention.
Solution Approach 2:
The system creates a template cage structure that serves as a reusable model for multiple avatar heads. Instead of manually creating cages for each avatar, the system copies and adapts the template cage to different avatar meshes through automatic correspondence establishment. This copying approach maintains alignment accuracy while dramatically reducing time consumption compared to manual caging for each individual avatar.
2Manufacturing precision
If manual caging processes are used to align hairstyles and clothing with avatar mesh topology, then alignment accuracy is improved, but computational resources increase significantly
Solution Approach 1:
The system performs computationally intensive tasks in advance, including vertex correspondence identification, transformation matrix computation, and geometric relationship establishment. By completing these resource-intensive operations before the actual caging process, the system reduces real-time computational demands while maintaining high alignment accuracy when hairstyles and clothing are aligned to avatar meshes.
Solution Approach 2:
The template cage structure serves as a reusable computational model that can be copied and applied to multiple avatar heads without repeating the full computational process. This copying approach significantly reduces computational resource requirements compared to manual caging, as the system only needs to apply pre-computed transformations rather than performing complex alignment calculations for each individual avatar.
3Productivity
If automatic cage generation is used to reduce time and computational resources, then efficiency is improved, but alignment accuracy may deteriorate
Solution Approach 1:
The system introduces a template cage as an intermediary structure between the avatar mesh and the final caging result. This template cage serves as a mediator that facilitates automatic correspondence establishment through well-defined geometric relationships and transformation rules. The intermediary template enables efficient automatic generation while maintaining accuracy by providing a structured framework for alignment.
Solution Approach 2:
The system employs parameter-based transformation methods to automatically adjust the template cage to match the target avatar mesh. By changing geometric parameters such as vertex positions, transformation matrices, and scaling factors based on computed correspondences, the system achieves accurate alignment automatically. These parameter adjustments maintain precision while enabling high-speed automatic generation without manual intervention.
Data Source
AI summary
According to one aspect of the present disclosure, a computer-implemented method of cage generation for animation is provided. The method may include identifying, by a processor, a correspondence between an input geometry of an avatar head and a template cage. The method may include generating, by the processor, an initial cage based on the correspondence. The method may include generating, by the processor, a final cage by adjusting a shape of the initial cage based on input geometry of the avatar head. The method may include animating, by the processor, the avatar head based on the input geometry and the final cage.