作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2012, Vol. 38 ›› Issue (08): 16-18. doi: 10.3969/j.issn.1000-3428.2012.08.006

• 博士论文 • 上一篇    下一篇

基于深度图像技术的手势识别方法

曹雏清,李瑞峰,赵立军   

  1. (哈尔滨工业大学机器人技术与系统国家重点实验室,哈尔滨 150001)
  • 收稿日期:2011-07-11 出版日期:2012-04-20 发布日期:2012-04-20
  • 作者简介:曹雏清(1982-),男,博士研究生,主研方向:模式识别,人机交互;李瑞峰,教授、博士生导师;赵立军,讲师
  • 基金资助:

    国家自然科学基金资助项目(61075081);机器人技术与 系统国家重点实验室课题基金资助项目(SKLRS200802A02)

Hand Posture Recognition Method Based on Depth Image Technoloy

CAO Chu-qing, LI Rui-feng, ZHAO Li-jun   

  1. (State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China)
  • Received:2011-07-11 Online:2012-04-20 Published:2012-04-20

摘要: 针对复杂环境下的手势识别问题,提出一种基于深度图像技术的手势识别方法。利用深度图像信息从复杂环境中提取手势区域,综合手势的表观特征,建立决策树实现手势的识别。对常见的9种手势在复杂背景条件下进行测试,实验结果表明,手势的平均识别率可达到98.4%,速度达到每秒25帧。

关键词: 手势识别, 深度图像, 表观特征, 复杂背景, 决策树

Abstract: Aiming at the problem of hand posture recognition from complex backgrounds, this paper proposes a hand posture recognition method based on depth image technoloy. The hand posture region is extracted from complex background via depth image. Appearance features are integrated to build the decision tree for hand posture recognition. Nine common postures with complex background are tested. Experimental results demonstrate that recognition rate is 98.4% and speed rate achieves 25 frames per second.

Key words: hand posture recognition, depth image, appearance feature, complex background, decision tree

中图分类号: