Static Hand Gesture Recognition Based on HOG with Kinect

摘要：

In this paper, we propose and implement a novel method for recognition static hand gestures using depth data from Kinect sensor of Microsoft. Compared to the entire human body, the hand is a smaller object with more complex articulations and more easily affected by segmentation errors. So it is a very challenging problem to recognize hand gestures. Our approach involves choosing HOG feature with both geometric moment invariant features and adapted to the light transform by analyzing the features of hands characteristics. Through the rapid cascade Adaboost training algorithm obtains the training models of gestures and matches them, thus build the accuracy and efficiency hand gesture recognition system using the Kinect sensor.

关键词： Static Hand Gesture Recognition Kinect Sensor HOG Adaboost learning algorithm

作者: Hui Li Lei Yang Xiaoyu Wu Shengmiao Xu Youwen Wang

作者单位: Digital Media Department, Communication University of China, Beijing, China

会议类型: 国际会议

会议名称: 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics 第4届智能人机系统与控制论国际会议 IHMSC 2012

会议地点: 南昌

会议语种:英文

页码: 271-273

在线出版日期: 2012-08-26（万方平台首次上网日期，不代表论文的发表时间）