  Importance of structured-light based one-shot scanning technique is
increasing because of its simple system configuration and ability of capturing
moving objects. One severe limitation of the technique is that it can capture
only sparse shape, but not high frequency shapes, because certain area of
projection pattern is required to encode spatial information. In this paper, we
propose a technique to recover high-frequency shapes by using shading
information, which is captured by one-shot RGB-D sensor based on structured
light with single camera. Since color image comprises shading information of
object surface, high-frequency shapes can be recovered by shape from shading
techniques. Although multiple images with different lighting positions are
required for shape from shading techniques, we propose a learning based
approach to recover shape from a single image. In addition, to overcome the
problem of preparing sufficient amount of data for training, we propose a new
data augmentation method for high-frequency shapes using synthetic data and
domain adaptation. Experimental results are shown to confirm the effectiveness
of the proposed method.
