Emerging Metaverse applications demand reliable, accurate, and photorealistic reproductions of human hands to perform sophisticated operations as if in the physical world. While real human hand represents one of the most intricate coordination between bones, muscle, tendon, and skin, state-of-the-art techniques unanimously focus on modeling only the skeleton of the hand. In this paper, we present NIMBLE, a novel parametric hand model that includes the missing key components, bringing 3D hand model to a new level of realism. We first annotate muscles, bones and skins on the recent Magnetic Resonance Imaging hand (MRI-Hand) dataset and then register a volumetric template hand onto individual poses and subjects within the dataset. NIMBLE consists of 20 bones as triangular meshes, 7 muscle groups as tetrahedral meshes, and a skin mesh. Via iterative shape registration and parameter learning, it further produces shape blend shapes, pose blend shapes, and a joint regressor. We demonstrate applying NIMBLE to modeling, rendering, and visual inference tasks. By enforcing the inner bones and muscles to match anatomic and kinematic rules, NIMBLE can animate 3D hands to new poses at unprecedented realism. To model the appearance of skin, we further construct a photometric HandStage to acquire high-quality textures and normal maps to model wrinkles and palm print. Finally, NIMBLE also benefits learning-based hand pose and shape estimation by either synthesizing rich data or acting directly as a differentiable layer in the inference network.
翻译:新兴的元体应用要求以可靠、准确和摄影现实的方式复制人体手部,以便像在物理世界一样执行复杂的操作。虽然真正的人体手是骨骼、肌肉、毛骨、肌肤和皮肤之间最复杂的协调,但最先进的技术一致侧重于仅模拟手的骨骼。在本文中,我们展示了NNNBleble,一个包含缺失的关键部件的新颖的比喻手型模型,将3D手型模型带到新的现实主义水平。我们首先在最新的磁共振成像手(MRI-Hand)数据集上注解肌肉、骨骼和皮肤,然后将体积模模模模模的手模模模模模手对单个和主题进行注册。通过将正常的骨骼和肌质结构的20个骨骼作为三角体形,7个肌肉组作为四面体形模模,以及一个皮肤模模组的模组注册和参数学习,进一步生成混合模型形状、可变形形状和组合体形体形体形,我们演示NNNBle-moble 动作、制和视觉变形图的动作和视觉任务。通过将内骨质结构和皮肤结构结构结构结构结构结构结构结构结构结构结构结构结构结构结构结构的精质的精质的精度直接构造和结构图图图图图图图图图图图图图图图,再构建成。