Hand Gestures Recognition Model for Augmented Reality Robotic Applications-Reference-Cited by-同舟云学术

Hand Gestures Recognition Model for Augmented Reality Robotic Applications

Published:2020-09-02 Issue: Volume: Page:187-196
ISSN:2190-3018
Container-title:Proceedings of 15th International Conference on Electromechanics and Robotics "Zavalishin's Readings"
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Author:

Murhij Youshaa^ORCID,Serebrenny Vladimir

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-5580-0_15

Reference13 articles.

1. Ge, L., et al.: 3D hand shape and pose estimation from a single RGB image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 10833–10842 (2019)

2. Newell, A., Yang, K., Deng J.: Stacked hourglass networks for human pose estimation. In: European Conference on Computer Vision, pp. 483–499 (2016)

3. Defferrard, M., Bresson, X., Vandergheynst, P.: Convolutional neural networks on graphs with fast localized spectral filtering. Adv. Neural Inf. Process. Syst. 3844–3852 (2016)

4. Cai, Y., Ge, L., Cai, J., Yuan, J.: Weakly-supervised 3d hand pose estimation from monocular RGB images. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 666–682 (2018)

5. Murhij, Y., Serebrenny, V.: An application to simulate and control industrial robot in virtual reality environment integrated with IR stereo camera sensor. IFAC-PapersOnLine 52(25), 203–207 (2019). https://doi.org/10.1016/j.ifacol.2019.12.473

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