Personalized Hand Modeling from Multiple Postures with Multi‐View Color Images
Personalized Hand Modeling from Multiple Postures with Multi‐View Color Images
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DOI：
10.1111/cgf.14149
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发表时间：
2020-10
影响因子：
2.5
通讯作者：
Yangang Wang;Ruting Rao;C. Zou
中科院分区：
文献类型：
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作者：
Yangang Wang;Ruting Rao;C. Zou
个性化的手部模型可以用来合成高质量的手部数据集，为深度学习提供更多可能的训练数据，并提高手部姿态估计的准确性。近年来，参数化的手模型，例如，MANO被广泛用于获得个性化的手模型。然而，现有的参数化手部模型分辨率较低，难以获得高逼真度的个性化手部模型。在本文中，我们提出了一种新的方法，通过多视图彩色图像从多个手部姿势估计个性化手部模型。个性化的手模型由个性化的中性手和多个手部姿势表示。我们提出了一种新的优化策略来估计中立的手从多个手的姿态。为了证明我们的方法的性能，我们构建了一个多视图系统，并捕获了超过35个人，每个人都有30个手势。我们希望估计的手模型可以推动未来高保真参数化手建模的研究。所有的手模型都可以在www.yangangwang.com上公开获得。
Personalized hand models can be utilized to synthesize high quality hand datasets, provide more possible training data for deep learning and improve the accuracy of hand pose estimation. In recent years, parameterized hand models, e.g., MANO, are widely used for obtaining personalized hand models. However, due to the low resolution of existing parameterized hand models, it is still hard to obtain high‐fidelity personalized hand models. In this paper, we propose a new method to estimate personalized hand models from multiple hand postures with multi‐view color images. The personalized hand model is represented by a personalized neutral hand, and multiple hand postures. We propose a novel optimization strategy to estimate the neutral hand from multiple hand postures. To demonstrate the performance of our method, we have built a multi‐view system and captured more than 35 people, and each of them has 30 hand postures. We hope the estimated hand models can boost the research of high‐fidelity parameterized hand modeling in the future. All the hand models are publicly available on www.yangangwang.com.