Single-Camera 3D Head Fitting for Mixed Reality Clinical Applications
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Abstract (arXiv)
We address the problem of estimating the shape of a person's head, defined as the geometry of the complete head surface, from a video taken with a single moving camera, and determining the alignment of the fitted 3D head for all video frames, irrespective of the person's pose. 3D head reconstructions commonly tend to focus on perfecting the face reconstruction, leaving the scalp to a statistical approximation. Our goal is to reconstruct the head model of each person to enable future mixed reality applications. To do this, we recover a dense 3D reconstruction and camera information via structure-from-motion and multi-view stereo. These are then used in a new two-stage fitting process to recover the 3D head shape by iteratively fitting a 3D morphable model of the head with the dense reconstruction in canonical space and fitting it to each person's head, using both traditional facial landmarks and scalp features extracted from the head's segmentation mask. Our approach recovers consistent geometry for varying head shapes, from videos taken by different people, with different smartphones, and in a variety of environments from living rooms to outdoor spaces.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 16 of its 45 references that are in the map. First posted on arXiv 6 Sep 2021.
Builds on
16 of 45 references.
References · 16
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4 more
- 2018Video to Fully Automatic 3D Hair Modelcited by 12
- 2017Sparse Photometric 3D Face Reconstruction Guided by Morphable Modelscited by 10
- 2018HairNet: Single-View Hair Reconstruction using Convolutional Neural Networkscited by 4
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Citing papers per year: 2023: 1; 2024: 0; 2025: 1.
2 papers.