A Multi-View Texture Fusion Approach for High Quality 3D Face Modelling

Bing-chuan LI, Yu-ping YE, Zhan SONG, Ling-sheng KONG, Su-ming TANG


This paper presents an accurate means for the 3D face texture mapping based on a multiple-view 3D scanning system. Given a reconstructed 3D mesh model and a set of calibrated images, a high-quality texture mosaic of the surface can be created by the proposed method. The proposed method aims to avoid noticeable seams, color discontinuity and ghosting problems. The method performs in two steps, i.e. occlusion areas filtering and the fusion of different texture images. The filtering is performed to identity invisible areas from the camera viewpoint and leaves them not textured. To perform the occluded areas filtering, we combine the geometrical features of the objects and the visual range of the camera. Experimental results showed that, texture mapping quality and precision can be improved in comparison with conventional means.


Texture mapping, Multi-view reconstruction, Visibility analysis


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