Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

3D face reconstruction with geometry details from a single image

Jiang, Luo, Zhang, Juyong, Deng, Bailin ORCID: https://orcid.org/0000-0002-0158-7670, Li, Hao and Liu, Ligang 2018. 3D face reconstruction with geometry details from a single image. IEEE Transactions on Image Processing 27 (10) , pp. 4756-4770. 10.1109/TIP.2018.2845697

[thumbnail of SingleImageReconstruction_v2-full.pdf]
Preview
PDF - Accepted Post-Print Version
Download (6MB) | Preview

Abstract

3D face reconstruction from a single image is a classical and challenging problem with wide applications in many areas. Inspired by recent works in face animation from RGB-D or monocular video inputs, we develop a novel method for reconstructing 3D faces from unconstrained 2D images using a coarse-to-fine optimization strategy. First, a smooth coarse 3D face is generated from an example-based bilinear face model by aligning the projection of 3D face landmarks with 2D landmarks detected from the input image. Afterward, using local corrective deformation fields, the coarse 3D face is refined using photometric consistency constraints, resulting in a medium face shape. Finally, a shape-from-shading method is applied on the medium face to recover fine geometric details. Our method outperforms the state-of-the-art approaches in terms of accuracy and detail recovery, which is demonstrated in extensive experiments using real-world models and publicly available data sets.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Computer Science & Informatics
Publisher: Institute of Electrical & Electronic Engineers
ISSN: 1057-7149
Date of First Compliant Deposit: 15 June 2018
Date of Acceptance: 4 June 2018
Last Modified: 07 Nov 2023 11:04
URI: https://orca.cardiff.ac.uk/id/eprint/112502

Citation Data

Cited 94 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics