Abstract
3D face clones can be used as pretreatments in many applications, such as emotion analysis. However, such clones should model facial shape accurately, while keeping the attributes of individuals; and they should be semantic. A clone is semantics when we know the position of the different parts of the face (eyes, nose...). The main problem of texture reconstruction methods is the seam appearance on fusion texture data. In our technique, we use a low cost RGB-D sensor to get an accurate and detailed facial unfolded texture. We use shape and texture patches to preserve the person’s characteristics. They are detected using an error distance and the direction of the normal vectors computed from the depth frames. The tests we perform show the robustness and the accuracy of our method.
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This research has been conducted with the support of Miles (FUI project) and Brittany Region (ARED).
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Manceau, J., Séguier, R., Soladié, C. (2015). Reconstruction of Face Texture Based on the Fusion of Texture Patches. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_35
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DOI: https://doi.org/10.1007/978-3-319-27857-5_35
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