Statistical Blendshape Calculation and Analysis for Graphics Applications

Fuente: arXiv
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Main Authors: Li, Shuxian, Wang, Tianyue, Twombly, Chris
Format: Preprint
Published: 2026
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author Li, Shuxian
Wang, Tianyue
Twombly, Chris
author_facet Li, Shuxian
Wang, Tianyue
Twombly, Chris
contents With the development of virtualization and AI, real-time facial avatar animation is widely used in entertainment, office, business and other fields. Against this background, blendshapes have become a common industry animation solution because of their relative simplicity and ease of interpretation. Aiming for real-time performance and low computing resource dependence, we independently developed an accurate blendshape prediction system for low-power VR applications using a standard webcam. First, blendshape feature vectors are extracted through affine transformation and segmentation. Through further transformation and regression analysis, we were able to identify models for most blendshapes with significant predictive power. Post-processing was used to further improve response stability, including smoothing filtering and nonlinear transformations to minimize error. Experiments showed the system achieved accuracy similar to ARKit 6. Our model has low sensor/hardware requirements and realtime response with a consistent, accurate and smooth visual experience.
format Preprint
id arxiv_https___arxiv_org_abs_2601_08234
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Statistical Blendshape Calculation and Analysis for Graphics Applications
Li, Shuxian
Wang, Tianyue
Twombly, Chris
Graphics
Human-Computer Interaction
With the development of virtualization and AI, real-time facial avatar animation is widely used in entertainment, office, business and other fields. Against this background, blendshapes have become a common industry animation solution because of their relative simplicity and ease of interpretation. Aiming for real-time performance and low computing resource dependence, we independently developed an accurate blendshape prediction system for low-power VR applications using a standard webcam. First, blendshape feature vectors are extracted through affine transformation and segmentation. Through further transformation and regression analysis, we were able to identify models for most blendshapes with significant predictive power. Post-processing was used to further improve response stability, including smoothing filtering and nonlinear transformations to minimize error. Experiments showed the system achieved accuracy similar to ARKit 6. Our model has low sensor/hardware requirements and realtime response with a consistent, accurate and smooth visual experience.
title Statistical Blendshape Calculation and Analysis for Graphics Applications
topic Graphics
Human-Computer Interaction
url https://arxiv.org/abs/2601.08234