Li Bai, Yi Song



AbstractThis paper presents a new approach to automatic 3D face recognition using a model-based approach. This work uses real 3D dense point cloud data acquired with a stereo face scanner. Since the point clouds are in varied orientations, by applying a non-iterative registration technique, we automatically transform each point cloud to a canonical position and detect facial features used for defining the frontal part of face which is to be modelled in next step. Unlike the iterative ICP algorithm, our non-iterative registration process is scale invariant. An efficient B-spline surface-fitting technique is developed to represent 3D faces in a way that allows efficient surface comparison. This is based on a novel knot vector standardisation algorithm to allow one-to-one mapping from the object space to a parameter space. Consequently, correspondence between objects is established based on shape descriptors, which can be used for recognition.


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Paper Citation

in Harvard Style

Bai L. and Song Y. (2006). 3D REGISTRATION AND MODELLING FOR FACE RECOGNITION . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 972-8865-40-6, pages 201-208. DOI: 10.5220/0001371002010208

in Bibtex Style

author={Li Bai and Yi Song},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},

in EndNote Style

JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
SN - 972-8865-40-6
AU - Bai L.
AU - Song Y.
PY - 2006
SP - 201
EP - 208
DO - 10.5220/0001371002010208