A coarse-to-fine curvature analysis-based rotation invariant 3D face landmarking

Przemyslaw Szeptycki 1 Mohsen Ardabilian 1 Liming Chen 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Automatic 2.5D face landmarking aims at locating facial feature points on 2.5D face models, such as eye corners, nose tip, etc. and has many applications ranging from face registration to facial expression recognition. In this paper, we propose a rotation invariant 2.5D face landmarking solution based on facial curvature analysis combined with a generic 2.5D face model and make use of a coarse-to-fine strategy for more accurate facial feature points localization. Experimented on more than 1600 face models randomly selected from the FRGC dataset, our technique displays, compared to a ground truth from a manual 3D face landmarking, a 100% of good nose tip localization in 8 mm precision and 100% of good localization for the eye inner corner in 12 mm precision.
Document type :
Conference papers
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01437805
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Tuesday, January 17, 2017 - 1:59:59 PM
Last modification on : Thursday, November 21, 2019 - 2:21:37 AM

Identifiers

Citation

Przemyslaw Szeptycki, Mohsen Ardabilian, Liming Chen. A coarse-to-fine curvature analysis-based rotation invariant 3D face landmarking. International Conference on Biometrics: Theory, Applications and Systems, Sep 2009, Washington, United States. pp.1-6, ⟨10.1109/BTAS.2009.5339052⟩. ⟨hal-01437805⟩

Share

Metrics

Record views

514