Abstract
We present a fully automatic approach to real-time 3D face reconstruction from monocular in-the-wild videos. With the use of a cascaded-regressor-based face tracking and a 3D morphable face model shape fitting, we obtain a semidense 3D face shape. We further use the texture information from multiple frames to build a holistic 3D face representation from the video footage. Our system is able to capture facial expressions and does not require any person-specific training. We demonstrate the robustness of our approach on the challenging 300 Videos in the Wild (300-VW) dataset. Our real-time fitting framework is available as an open-source library at http://4dface.org.
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Huber, P., Kopp, P., Christmas, W., Ratsch, M., & Kittler, J. (2017). Real-Time 3D face fitting and texture fusion on in-the-wild videos. IEEE Signal Processing Letters, 24(4), 437–441. https://doi.org/10.1109/LSP.2016.2643284
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