39-Issue 7

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https://diglib.eg.org/handle/10.2312/2632946

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Browsing 39-Issue 7 by Subject "Computer graphics"

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    Personalized Hand Modeling from Multiple Postures with Multi-View Color Images
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Wang, Yangang; Rao, Ruting; Zou, Changqing; Eisemann, Elmar and Jacobson, Alec and Zhang, Fang-Lue
    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 highfidelity parameterized hand modeling in the future. All the hand models are publicly available on www.yangangwang.com.
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    Two-stage Resampling for Bidirectional Path Tracing with Multiple Light Sub-paths
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Nabata, Kosuke; Iwasaki, Kei; Dobashi, Yoshinori; Eisemann, Elmar and Jacobson, Alec and Zhang, Fang-Lue
    Recent advances in bidirectional path tracing (BPT) reveal that the use of multiple light sub-paths and the resampling of a small number of these can improve the efficiency of BPT. By increasing the number of pre-sampled light sub-paths, the possibility of generating light paths that provide large contributions can be better explored and this can alleviate the correlation of light paths due to the reuse of pre-sampled light sub-paths by all eye sub-paths. The increased number of pre-sampled light subpaths, however, also incurs a high computational cost. In this paper, we propose a two-stage resampling method for BPT to efficiently handle a large number of pre-sampled light sub-paths. We also derive a weighting function that can treat the changes in path probability due to the two-stage resampling. Our method can handle a two orders of magnitude larger number of presampled light sub-paths than previous methods in equal-time rendering, resulting in stable and better noise reduction than state-of-the-art methods.