A natural and synthetic corpus for benchmarking of hand gesture recognition systems-Reference-Cited by-同舟云学术

A natural and synthetic corpus for benchmarking of hand gesture recognition systems

Published:2013-11-13 Issue:4 Volume:25 Page:943-954
ISSN:0932-8092
Container-title:Machine Vision and Applications
language:en
Short-container-title:Machine Vision and Applications

Author:

Molina Javier,Pajuelo José A.,Escudero-Viñolo Marcos,Bescós Jesús,Martínez José M.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

http://link.springer.com/content/pdf/10.1007/s00138-013-0576-z.pdf

Reference25 articles.

1. Causo, A., Matsuo, M., Ueda, E., Takemura, K., Matsumoto, Y., Takamatsu, J., Ogasawara, T.: Hand pose estimation using voxel-based individualized hand model. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2009. AIM 2009, pp. 451–456 (2009)

2. Causo, A., Ueda, E., Kurita, Y., Matsumoto, Y., Ogasawara, T.: Model-based hand pose estimation using multiple viewpoint silhouette images and unscented kalman filter. In: The 17th IEEE International Symposium on Robot and Human Interactive Communication, 2008. RO-MAN 2008 , pp. 291–296 (2008)

3. Dadgostar, F., Barczak, A.L.C., Sarrafzadeh, A.: A color hand gesture database for evaluating and improving algorithms on hand gesture and posture recognition. Res. Lett. Inf. Math. Sci. 7, 127–134 (2005)

4. Erol, A., Bebis, G., Nicolescu, M., Boyle, R.D., Twombly, X.: Vision-based hand pose estimation: a review. Comput. Vis. Image Underst. 108(1–2), 52–73 (2007)

5. Ge, S., Yang, Y., Lee, T.: Hand gesture recognition and tracking based on distributed locally linear embedding. In: IEEE Conference on Robotics, Automation and Mechatronics, 2006, pp. 1–6 (2006)

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