基于Kinect的动态孤立手势识别研究  

Research on Dynamic Isolated Gesture Recognition Based on Kinect

作　　者：田喜平[1] 赵红丹[2] 

机构地区：[1]安阳师范学院软件学院,河南安阳455000 [2]安阳师范学院计算机与信息工程学院,河南安阳455000

出　　处：《微电子学与计算机》2017年第2期115-118,共4页Microelectronics & Computer

基　　金：国家自然科学基金项目(60875081);安阳师范学院科研培育基金项目(AYNU-KP-B09)

摘　　要：当前方法对动态孤立手势的识别,过程复杂、成本高,动态手势的移动轨迹易受到外界环境的干扰、识别准确率低.提出了基于Kinect的动态孤立手势识别方法,利用Kinect传感器获取动态手势信息,对人体手部进行实时、准确的定位跟踪,并对手部图像进行平滑去噪处理,提取动态手势轨迹的特征;引入隐马尔可夫模型(HMM)对动态孤立手势及手部运动轨迹的样本集进行有效训练,最终实现动态孤立手势的精确识别.实验证明提出的方法在噪声干扰和光线缺失的环境下,对动态孤立手势仍具有较高的识别率,鲁棒性强.Traditional methods for the extraction and identification of the data of dynamic isolated gestures, which constitute a complex and high cost, which is easy to be disturbed by the external environment, and the recognition accuracy is low. The study of dynamic hand gesture recognition method based on Kinect, obtaining the depth information of dynamic gesture using Kinect sensor, the human hand positioning real-time and accurate tracking, feature and image denoising processing, the extraction of hand movement; finally introduce the hidden Markov model （HMM） for effective training on dynamic gesture and moving track sample set, to achieve dynamic hand gesture recognition. Experiments show that the proposed method has high recognition rate and high robustness in the environment of noise interference and light loss.

关 键 词：KINECT 手势识别 HMM 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]