IET Computer Vision
Special Issue on
3D Face Processing
Estimating 3D face shape from one or more images is a longstanding
goal of computer vision. In the earliest work on shape-from-shading,
researchers applied their algorithms to face images with little
success. Advances during the last decade have seen the development of
techniques that offer robust performance on real world
images. Meanwhile, advances in structured light scanning and other
non-standard sensing modalities have made high-end acquisition of 3D
structure and motion a reality, albeit in controlled settings. A clear
result to come from this work is that the processing of 3D face data
requires techniques that span a number of fields. These include
statistical shape modelling, non-linear optimisation, reflectance
modelling, illumination estimation and shape-from-shading. These
advances hold out the hope of estimating intrinsic properties of a
face from single images or video streams. This is clearly attractive
in the domain of face recognition where modelling appearance variation
caused by large changes in pose, illumination and expression remains a
key problem. Applications also lie in model acquisition for graphics
applications, retouching faces in images (for example, adjusting
expressions or illumination conditions) or even exchanging faces
between images.

This Special Issue is associated with the workshop on “3D Face
Processing” held in conjunction with the IEEE Computer Society
Conference on Computer Vision and Pattern Recognition (CVPR) held in
Anchorage, Alaska in June 2008. Therefore, contributors to the
workshop are particularly invited to submit papers. However,
contribution to this Special Issue is open to all researchers working
in the field and they are strongly encouraged to make a submission.

Topics of interest include, but are not limited to, the following:

. 3D morphable face models . 2D+3D active appearance models
. Face/skin reflectance modelling .

. Facial shape-from-shading and photometric stereo . Stereo for face
images .

. Psychological or neuropsychological investigations into the role 3D
information plays in face processing in humans .

. Structured light/Shape-from-X for face shape recovery . Estimation
of illumination or shadowing from images .

. Modelling variation in appearance due to 3D shape using spherical
harmonics, light fields etc .

. Dynamic 3D face processing in video images, e.g. tracking, modelling
of expressions in 3D, use of motion capture data .

. Real-time 3D face scanning from video . Colour information for 3D
face processing .

. Fusion of multimodal face information, e.g. 3D scans, high-speed
video, high-resolution imaging .

. Data management for large 3D face data sets . Matching of partial or
deformed scans .

Applications of interest include:

. Facial shape estimation . Recognition/classification using 3D
information estimates from images .

. Facial retouching, expression/texture transfer, relighting using 3D
models .

. Medical applications of 3D face modelling and facial expression
analysis .

Paper Format and Submission : Papers must be typed in a font size no
smaller than 10 pt, and presented in single-column format with double
line spacing on one side A4 paper. All pages should be numbered. The
manuscript should be formatted according to the IET Proceedings
requirements, typically 4000-6000 words long with 6-10
Figures. Detailed information about IET Research Journals, including
an author guide and formatting information is available at:
http://www.theiet.org/publications/journals/ All papers must be
submitted through the journal’s Manuscript Central system: http://mc.manuscriptcentral.com/iet-ipr
When uploading your paper, please ensure that your manuscript is
marked as being for this special issue.
Important Dates:
Submission: Sept 26, 2008
First Decision: Dec 31, 2008
Revised Manuscript: Mar 2009
Publication: June 2009
Guest Editors:
Prof. Volker Blanz, University of Siegen
Dr. Baback Moghaddam, California Institute of Technology
Prof. Hanspeter Pfister, Harvard School of Engineering
Prof. Dimitris Samaras, Stony Brook University
Dr. William Smith, University of York