ML Anthology

Measuring Grasp Posture Using an Embedded Camera

Naoaki Kashiwagi, Yuta Sugiura, Natsuki Miyata, Mitsunori Tada, Maki Sugimoto, Hideo Saito
WACVW 2017 pp. 42-47
doi:10.1109/WACVW.2017.14 /wacvw/2017/kashiwagi2017wacvw-measuring/

Abstract

This paper proposes a measurement system for grasping postures using a fish eye camera. We attached a fish eye camera to the cap of a cylindrical object, such as a jar or a bottle. The fish eye camera was used to determine the position of the fingertips in 3D via image processing. The grasping posture utilized when opening or closing ajar or a bottle was then reconstructed. If an object, a model of a hand and the grasp type are given, it is possible to estimate the grasping posture of the whole hand, even using partially captured data. Preliminary experimental results show that the system is able to reconstruct the grasping posture of various users.

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Cite

Text

Kashiwagi et al. "Measuring Grasp Posture Using an Embedded Camera." IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2017. doi:10.1109/WACVW.2017.14

Markdown

[Kashiwagi et al. "Measuring Grasp Posture Using an Embedded Camera." IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2017.](https://mlanthology.org/wacvw/2017/kashiwagi2017wacvw-measuring/) doi:10.1109/WACVW.2017.14

BibTeX

@inproceedings{kashiwagi2017wacvw-measuring,
  title     = {{Measuring Grasp Posture Using an Embedded Camera}},
  author    = {Kashiwagi, Naoaki and Sugiura, Yuta and Miyata, Natsuki and Tada, Mitsunori and Sugimoto, Maki and Saito, Hideo},
  booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision Workshops},
  year      = {2017},
  pages     = {42-47},
  doi       = {10.1109/WACVW.2017.14},
  url       = {https://mlanthology.org/wacvw/2017/kashiwagi2017wacvw-measuring/}
}