Dynamic projection mapping for a moving object according to its position and shape is fundamental for augmented reality to resemble changes on a target surface. For instance, augmenting the human arm surface via dynamic projection mapping can enhance applications in fashion, user interfaces, prototyping, education, medical assistance, and other fields. For such applications, however, conventional methods neglect skin deformation and have a high latency between motion and projection, causing noticeable misalignment between the target arm surface and projected images. These problems degrade the user experience and limit the development of more applications. We propose a system for high-speed dynamic projection mapping onto a rapidly moving human arm with realistic skin deformation. With the developed system, the user does not perceive any misalignment between the arm surface and projected images. First, we combine a state-of-the-art parametric deformable surface model with efficient regression-based accuracy compensation to represent skin deformation. Through compensation, we modify the texture coordinates to achieve fast and accurate image generation for projection mapping based on joint tracking. Second, we develop a high-speed system that provides a latency between motion and projection below 10 ms, which is generally imperceptible by human vision. Compared with conventional methods, the proposed system provides more realistic experiences and increases the applicability of dynamic projection mapping.
Self-organizing Deformable Model : a Method for Projecting a 3D Object Mesh Model onto a Target Surface