Interactive Model-based Reconstruction of the Human Head using an RGB-D Sensor

We present a novel method for the interactive markerless reconstruction of human heads using a single commodity RGB-D sensor. Our entire reconstruction pipeline is implemented on the graphics processing unit and allows to obtain high-quality reconstructions of the human head using an interactive and intuitive reconstruction paradigm. The core of our method is a fast graphics processing unit-based nonlinear quasi-Newton solver that allows us to leverage all information of the RGB-D stream and fit a statistical head model to the observations at interactive frame rates. By jointly solving for shape, albedo and illumination parameters, we are able to reconstruct high-quality models including illumination corrected textures. All obtained reconstructions have a common topology and can be directly used as assets for games, films and various virtual reality applications. We show motion retargeting, retexturing and relighting examples. The accuracy of the presented algorithm is evaluated by a comparison against ground truth data.

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