Various simulation applications for hair, clothing, and makeup of a 3D avatar can provide more useful information to users before they select a hairstyle, clothes, or cosmetics. To enhance their reality, the shapes, textures, and colors of the avatars should be similar to those found in the real world. For a more realistic 3D avatar color reproduction, this paper proposes a spectrum-based color reproduction algorithm and color management process with respect to the implementation of the algorithm. First, a makeup color reproduction model is estimated by analyzing the measured spectral reflectance of the skin samples before and after applying the makeup. To implement the model for a makeup simulation system, the color management process controls all color information of the 3D facial avatar during the 3D scanning, modeling, and rendering stages. During 3D scanning with a multicamera system, spectrum-based camera calibration and characterization are performed to estimate the spectrum data. During the virtual makeup process, the spectrum data of the 3D facial avatar is modified based on the makeup color reproduction model. Finally, during 3D rendering, the estimated spectrum is converted into RGB data through gamut mapping and display characterization.

Rapid industrialization has significantly influenced people’s lifestyles in the recent decades, and the influence of traditional culture is diminishing. Recently, several studies attempted to simultaneously utilize various sensors to record delicate and sophisticated performances of intangible cultural heritage (ICH). Although painting is one of the most common ICH of human history, few research studies have recorded traditional painting work. In this paper, we aim to lay the groundwork for reviving Korean painting, even if there would be no painters to produce these traditional Korean paintings in the future. We propose a novel multisensor-based acquisition system that records traditional Korean painting work while minimizing interference in the work. The proposed system captures real-time data originating from the painter, brushes, pigments, and canvas, which are the essential components of the painting work. We utilized the proposed system to capture the painting work by two experts, and we visualize the captured data. We showed the various results of statistical analysis, and also discussed the usability.

Figure 1: Image-based wound mold making: (a) wound image, (b) gray image, (c) extracted features, (d) 2D wound mesh, (e) height map, (f) 3D wound mold model.