Hand-Shape Recognition Using the Distributions of Multi-Viewpoint Image Sets-Reference-Cited by-同舟云学术

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Hand-Shape Recognition Using the Distributions of Multi-Viewpoint Image Sets

Published:2012 Issue:6 Volume:E95.D Page:1619-1627
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

OHKAWA Yasuhiro¹,FUKUI Kazuhiro¹

Affiliation:

1. Graduate School of Systems and Information Engineering, University of Tsukuba

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E95.D/6/E95.D_1619/_pdf

Reference27 articles.

1. [1] A. Erol, G. Bebis, M. Nicolescu, R. Boyle, and X. Twombly, “Vision-based hand pose estimation: A review,” Comput. Vis. Image Understand., vol.108, no.1-2, pp.52-73, 2007.

2. [2] S. Ong and S. Ranganath, “Automatic sign language analysis: A survey and the future beyond lexical meaning,” IEEE Trans. Pattern Anal. Mach. Intell., vol.27, no.6, pp.873-891, 2005.

3. [3] B. Stenger, P. Mendonça, and R. Cipolla, “Model-based hand tracking using an unscented Kalman filter,” British Machine Vision Conference, vol.1, pp.63-72, 2001.

4. [4] B. Stenger, A. Thayananthan, P. Torr, and R. Cipolla, “Model-based hand tracking using a hierarchical Bayesian filter,” IEEE Trans. Pattern Anal. Mach. Intell., vol.28, no.9, pp.1372-1384, 2006.

5. [5] A. Imai, N. Shimada, and Y. Shirai, “Hand posture estimation in complex backgrounds by considering mis-match of model,” Asian Conference on Computer Vision, pp.596-607, 2007.

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