计算机科学 ›› 2015, Vol. 42 ›› Issue (9): 299-302.doi: 10.11896/j.issn.1002-137X.2015.09.059

• 图形图像与模式识别 • 上一篇    下一篇

基于深度图像的多学习者姿态识别

张鸿宇,刘威,许 炜,王 辉   

  1. 华中科技大学电子与信息工程系 武汉430074,华中科技大学电子与信息工程系 武汉430074,华中科技大学电子与信息工程系 武汉430074,华中科技大学电子与信息工程系 武汉430074
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家科技支撑计划项目(2013BAH72B01-1)资助

Depth Image Based Gesture Recognition for Multiple Learners

ZHANG Hong-yu, LIU Wei, XU Wei and WANG Hui   

  • Online:2018-11-14 Published:2018-11-14

摘要: 在数字化学习场景中,人体姿态的识别有助于分析学习者的学习状态。提出了一种基于深度图像的多学习者姿态识别方法。首先通过Kinect的红外传感器获取包含深度信息的图像,利用深度图像进行人像-背景分离;然后提取人体的轮廓特征Hu矩;最后采用SVM分类器对轮廓特征进行分类和识别。实验结果表明,本方法能有效地识别多个学习者的举手、正坐和低头等姿态。

关键词: 姿态识别,深度图像,多学习者

Abstract: Gesture recognition of the learner’s body is helpful for analysing and evaluating the learner’s status in the e-learning system.In this paper,a depth image based gesture recognition method was proposed to recognize multiple learners.After obtaining the depth image from Kinect sensor,the human body is separated from the background image and the contour features described in Hu moments are extracted.The learner’s gesture is then recognized based on SVM classifier.The test results show that this method can efficiently recognize the hand-up,sitting and head-yield gestures of multiple learners.

Key words: Gesture recognition,Depth image,Multiple learner

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