e-Restoration of Faces Appearing In Cultural Heritage Artefacts

Virtual restoration of Cultural Heritage (CH) artefacts is an important task that aims to re-create the original appearance of damaged items. In this paper we describe a method that can be used for virtual restoration of faces appearing in cultural heritage artefacts. Given a damaged face appearing in a 2D image we estimate the complete 3D shape of a face using data from the non-damaged face and we predict the texture of the damaged regions. As a result it is possible to generate a restored 3D model of the face which can be mapped back on the 2D image in order to complete the restoration process. Both visual and quantitative results prove the potential of the proposed method.

[1]  Aleix M. Martínez,et al.  Recognizing Imprecisely Localized, Partially Occluded, and Expression Variant Faces from a Single Sample per Class , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  T. Vetter,et al.  A statistical method for robust 3D surface reconstruction from sparse data , 2004 .

[3]  Mauro Barni,et al.  Image Processing for Virtual Restoration of Artworks , 2000, IEEE Multim..

[4]  Chrisina Draganova,et al.  Restoration of Partially Occluded Shapes of Faces Using Neural Networks , 2005, CORES.

[5]  Seong-Whan Lee,et al.  Reconstruction of Partially Damaged Face Images Based on a Morphable Face Model , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Raimondo Schettini,et al.  Detection and Restoration of Occlusions for 3D Face Recognition , 2006, 2006 IEEE International Conference on Multimedia and Expo.

[7]  Michael Petzet,et al.  Principles of preservation: An introduction to the International Charters for Conservation and Restoration 40 years after the Venice Charter , 2004 .

[8]  Mauro Barni,et al.  Image processing for the analysis and conservation of paintings: opportunities and challenges , 2005, IEEE Signal Process. Mag..

[9]  A. Del Mastio,et al.  Virtual Restoration and Protection of Cultural Heritage Images , 2007, 2007 15th International Conference on Digital Signal Processing.

[10]  Luc Van Gool,et al.  A Generalized EM Approach for 3D Model Based Face Recognition under Occlusions , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[11]  J. Tao,et al.  Reconstruction of Partially Occluded Face by Fast Recursive PCA , 2007, 2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007).

[12]  Harry Shum,et al.  Automatic eyeglasses removal from face images , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Paolo Cignoni,et al.  Visualization and 3D data processing in the David restoration , 2004, IEEE Computer Graphics and Applications.

[14]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[15]  Sang Chul Ahn,et al.  Glasses Removal from Facial Image Using Recursive PCA Reconstruction , 2003, AVBPA.

[16]  Takio Kurita,et al.  Recognition and detection of occluded faces by a neural network classifier with recursive data reconstruction , 2003, Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2003..

[17]  Timothy F. Cootes,et al.  Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Thomas Vetter,et al.  Face Recognition Based on Fitting a 3D Morphable Model , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Ioannis Pitas,et al.  Digital image processing techniques for the detection and removal of cracks in digitized paintings , 2006, IEEE Transactions on Image Processing.

[20]  Norishige Chiba,et al.  Locally Adaptive Chromatic Restoration of Digitally Acquired Paintings , 2005, Int. J. Image Graph..

[21]  Andreas Lanitis.  Person identification from heavily occluded face images , 2004, SAC '04.

[22]  J.-A. Beraldin.  Virtual Reconstruction of Heritage Sites: Opportunities and Challenges Created by 3D Technologies * , 2005 .