3D shape reconstruction of Mooney faces

Two-tone (ldquoMooneyrdquo) images seem to arouse vivid 3D percept of faces, both familiar and unfamiliar, despite their seemingly poor content. Recent psychological and fMRI studies suggest that this percept is guided primarily by top-down procedures in which recognition precedes reconstruction. In this paper we investigate this hypothesis from a mathematical standpoint. We show that indeed, under standard shape from shading assumptions, a Mooney image can give rise to multiple different 3D reconstructions even if reconstruction is restricted to the Mooney transition curve (the boundary curve between black and white) alone. We then use top-down reconstruction methods to recover the shape of novel faces from single Mooney images exploiting prior knowledge of the structure of at least one face of a different individual. We apply these methods to thresholded images of real faces and compare the reconstruction quality relative to reconstruction from gray level images.

[1]  Ron Kimmel,et al.  Optimal Algorithm for Shape from Shading and Path Planning , 2001, Journal of Mathematical Imaging and Vision.

[2]  Patrick Cavanagh,et al.  Recovery of 3D volume from 2-tone images of novel objects , 1998, Cognition.

[3]  Ales Leonardis,et al.  Recognizing 2-tone images in grey-level parametric eigenspaces , 2002, Pattern Recognit. Lett..

[4]  B. Renault,et al.  Face and shape repetition effects in humans: a spatio‐temporal ERP study , 1997, Neuroreport.

[5]  T. Kanade,et al.  Combining Models and Exemplars for Face Recognition: An Illuminating Example , 2001 .

[6]  Denis Schluppeck,et al.  Neural responses to Mooney images reveal a modular representation of faces in human visual cortex , 2004, NeuroImage.

[7]  Ira Kemelmacher-Shlizerman,et al.  Molding Face Shapes by Example , 2006, ECCV.

[8]  J A Sethian,et al.  A fast marching level set method for monotonically advancing fronts. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Jay Hegdé,et al.  Identifying faces in two-tone ('Mooney') images: A psychophysical and fMRI study , 2010 .

[10]  J. Tsitsiklis,et al.  Efficient algorithms for globally optimal trajectories , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[11]  Matthew Turk,et al.  A Morphable Model For The Synthesis Of 3D Faces , 1999, SIGGRAPH.

[12]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[13]  C. M. Mooney.  Age in the development of closure ability in children. , 1957, Canadian journal of psychology.

[14]  Anna R. Bruss.  The Eikonal equation: some results applicable to computer vision , 1982 .

[15]  F. Varela,et al.  Perception's shadow: long-distance synchronization of human brain activity , 1999, Nature.

[16]  Rama Chellappa,et al.  Characterization of Human Faces under Illumination Variations Using Rank, Integrability, and Symmetry Constraints , 2004, ECCV.

[17]  Sami Romdhani,et al.  Efficient, robust and accurate fitting of a 3D morphable model , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[18]  Jonathan Winawer,et al.  Mooney image perception in preschool-aged children , 2007 .

[19]  Edwin R. Hancock,et al.  A Coupled Statistical Model for Face Shape Recovery From Brightness Images , 2007, IEEE Transactions on Image Processing.

[20]  Paul A. Griffin,et al.  Statistical Approach to Shape from Shading: Reconstruction of Three-Dimensional Face Surfaces from Single Two-Dimensional Images , 1996, Neural Computation.

[21]  Ronen Basri,et al.  Lambertian reflectance and linear subspaces , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[22]  David J. Kriegman,et al.  From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Amnon Shashua,et al.  On Photometric Issues in 3D Visual Recognition from a Single 2D Image , 2004, International Journal of Computer Vision.

[24]  R. Basri,et al.  Statistical Symmetric Shape from Shading for 3D Structure Recovery of Faces , 2004, eccv 2004.

[25]  John Oliensis,et al.  Uniqueness in shape from shading , 1991, International Journal of Computer Vision.

[26]  P. Hanrahan,et al.  On the relationship between radiance and irradiance: determining the illumination from images of a convex Lambertian object. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.

[27]  J AtickJoseph,et al.  Statistical approach to shape from shading , 1996 .

[28]  Edwin R. Hancock,et al.  Recovering facial shape and albedo using a statistical model of surface normal direction , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[29]  Lei Zhang,et al.  Face recognition under variable lighting using harmonic image exemplars , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[30]  Karl J. Friston,et al.  How the brain learns to see objects and faces in an impoverished context , 1997, Nature.

[31]  K. Nakayama,et al.  The effect of face inversion on the human fusiform face area , 1998, Cognition.