Avatar JSON Capture Format for Reusable Photogrammetry Parameters
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Solution Overview
Problem
Current technologies lack a dedicated format for encoding capture rig parameters of avatars, requiring manual recapture or laborious artist work to correct or enhance avatar assets.
Innovation Solution
Introduces the Avatar JSON Interchange File (AJIF) format to encode and store capture rig parameters, allowing for the inclusion of additional properties about avatars, enabling efficient retrieval and utilization of raw data for improved rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a dedicated format for encoding capture rig parameters is not used, then data storage is simpler, but manual recapture or artist work is required to correct or enhance avatar assets
Solution Approach 1:
The patent applies preliminary action by encoding capture rig parameters (intrinsic and extrinsic camera data, mesh photogrammetry settings) directly into the avatar asset file during the initial capture process. This allows all necessary correction data to be pre-prepared and stored with the avatar, eliminating the need for subsequent manual recapture or artist intervention to correct or enhance the asset.
2Manufacturing precision
If capture parameters are encoded in avatar data, then rendering can be enhanced, but data structure complexity increases
Solution Approach 1:
The patent applies segmentation by organizing capture parameters into distinct, structured sections within the avatar data: intrinsic parameters (camera focal length, aperture, sensor dimensions), extrinsic parameters (camera positions, rotations, translations), and mesh photogrammetry parameters (mesh density, subdivision levels). This segmented structure manages complexity through clear organization while preserving all rendering-enhancement data.
3Productivity
If manual artist work is required to correct avatar assets, then flexibility is maintained, but productivity decreases
Solution Approach 1:
The patent applies self-service by enabling automated correction and enhancement of avatar assets through the encoded capture parameters. Software systems can automatically retrieve intrinsic and extrinsic camera data, mesh photogrammetry settings, and rendering parameters from the structured data, performing corrections without requiring manual artist intervention while maintaining the flexibility to adjust parameters as needed.
Data Source
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AI summary
Some embodiments of a method may include: obtaining a plurality of images of a portion of a person; performing one or more mesh photogrametry processes on at least one of the plurality of images; transcoding an output of at least one of the one or more mesh photogrametry processes, wherein transcoding the output of at least one of the one or more mesh photogrametry processes generates a transcoder output; and performing a rendering process on the transcoder output to generate avatar data, wherein the avatar data comprises capture data corresponding to at least one of the mesh photogrametry processes.