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Human gait recognition based on deterministic learning and kinect sensor

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Human gait recognition based on deterministic learning and K...

基于kinect sensor的人体姿势识别研究

第30届中国控制与决策会议

作者： Hao Zhen Muqing Deng Peng Lin Cong Wang College of Automation Hangzhou Dianzi University College of Automation South China University of Technology

Model construction, fitting and feature extraction remain the main difficult tasks in model-based gait recognition methods. To develop an easy practical model-based gait recognition system, this paper invetigates the combined use of deterministic learning and Microsoft kinect sensor for human gait recognition. First, real-time data stream of human joints position are acquired by using Microsoft kinect and MATLAB toolbox. Second, four different time-varying gait feature are selected to represent human walking. Third, gait variability underlying different individuals’ time-varying gait features is effectively modeled by using deterministic learning algorithm. This kind of variability reflects the change of the walking information while preserving temporal dynamics information. Gait patterns are represented as the gait variability underlying time-varying gait features and a rapid recognition scheme is presented. Experimental results show that the combination of deterministic learning and Microsoft kinect sensor can provide an encouraging recognition accuracy.

关键词： Gait recognition Deterministic learning kinect sensor Gait variability

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基于Kinect sensor的人体姿势识别研究

作者：李玉明东北大学

学位级别：硕士

在过去的二十年里互联网和通信技术的飞速发展为当前物联网的发展奠定了基石,随之兴起的智能手机、可穿戴智能设备、智能汽车、虚拟现实设备已经逐步融入人们工作与生活的方方面面。传统的键盘、鼠标输入方式以及多点触控技术已经不能... 详细信息

在过去的二十年里互联网和通信技术的飞速发展为当前物联网的发展奠定了基石,随之兴起的智能手机、可穿戴智能设备、智能汽车、虚拟现实设备已经逐步融入人们工作与生活的方方面面。传统的键盘、鼠标输入方式以及多点触控技术已经不能完全满足人们的需求,人机交互又一次迎来了新的挑战。本文借助kinect的骨骼跟踪技术,设计基于kinect的人体姿势识别平台,对人机交互的体感技术方面进行了研究。首先,在学习kinect for windows SDK之后,利用kinect获取人体骨骼信息,对人体骨骼信息进行处理,建立人体骨骼向量。并将骨骼向量的三维角度分量以矩阵形式存储,建立人体姿势模板的数学模型。其次,建立人体姿势标准库,其中包括12个常见的人体标准姿势模板。在对标准姿势的骨骼信息进行分析后,为了降低骨骼向量间的耦合性以及计算复杂度,选择将人体姿势识别转换为肢体姿势识别,并提取各个肢体姿势的特征值。接着以肢体姿势特征值为基础,结合本文提出的基于骨骼向量特征值的模板匹配算法完成姿势分类器的设计,从而实现人体姿势识别。最后,通过在Visual studio 2010上编写程序,完成基于kinect的人体姿势识别平台,对平台进行调试与测试,主要包括错误调试和功能测试,其中人体姿势识别功能为重点测试项目。本文提出的基于骨骼向量特征值的模板匹配算法与kinect设备的骨骼跟踪技术结合较好的实现了人体姿势识别,识别率达到98%以上,有效的解决了人体姿势识别算法复杂度高,不易实现的问题。

关键词：人体姿势识别 kinect sensor 骨骼向量肢体姿势特征值模板匹配算法

Multi-camera systems for rehabilitation therapies:a study of the precision of Microsoft kinect sensors

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Frontiers of Information Technology & Electronic Engineering 2016年第4期17卷 348-364页

作者： Miguel OLIVER Francisco MONTERO Jose Pascual MOLINA Pascual GONZALEZ Antonio FERNANDEZ-CABALLERO Instituto de Investigacidn en Informdtica de Albacete Universidad de Castilla-La ManchaAlbacete 02071Spain Departamento de Sistemas Informaticos Universidad de Castilla-La ManchaAlbacete 02071Spain

This paper seeks to determine how the overlap of several infrared beams affects the tracked position of the user, depending on the angle of incidence of light, distance to the target, distance between sensors, and the number of capture devices used. We also try to show that under ideal conditions using several kinect sensors increases the precision of the data collected. The results obtained can be used in the design of telerehabilitation environments in which several RGB-D cameras are needed to improve precision or increase the tracking range. A numerical analysis of the results is included and comparisons are made with the results of other studies. Finally, we describe a system that implements intelligent methods for the rehabilitation of patients based on the results of the tests carried out.

关键词： kinect sensor Rehabilitation system Capture precision Multi-camera system

Evaluating the Effect of Various Walking Conditions on kinect-based Gait Recognition

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Instrumentation 2022年第2期9卷 13-25页

作者： LIU Ruixuan Marina L.GAVRILOVA Renmin University of China Beijing 100872China Biometric Technologies Laboratory University of CalgaryCanada

Human gait is one of the unobtrusive behavioral biometrics that has been extensively studied for various commercial and government *** security,medical rehabilitation,virtual reality,and autonomous driving cars are some of the fields of study that rely on accurate gait *** majority of studies have been focused on achieving very high recognition performance on a specific dataset,different issues arise in the real-world applications of this *** research is one of the first to evaluate the effects of changing walking speeds and directions on gait recognition rates under various walking *** was collected using the kinect *** draw an overall conclusion about the effects of walking speed and di-rection to the sensor,we define distance features and angle ***,we propose two feature fusion methods for person *** of the study provide insights into how walking speeds and walking di-rections to the kinect sensor influence the accuracy of gait recognition.

关键词： Gait Recognition kinect sensor Feature Fusion Walking Conditions Biometric Security

Rapid 3D human body modeling based on kinect technology

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Computer Aided Drafting,Design and Manufacturing 2013年第1期23卷 7-13页

作者： HE Kunlin XU Yong MAO Aihua LI Guiqing School of Computer Science and Engineering South China University of Technology

The 3D shape of the human body is useful for applications in fitness, games and apparel. Accurate body scanners, howev- er, are expensive, limiting the availability of 3D body models. In this paper, we focus on the human body 3D modeling using one kinect sensor modeling method. To get the human body model fast, three steps in rapid modeling of the human body are carried out. Firstly, according to anthropometric parameters, the standard model is parameterized; Secondly, the kinect depth image of the human body model is gotten through, then, by using the PCL library the point cloud data is processed and matched, and the human body model is optimized; Finally, the realistic human body model is obtained with the rapid integration of the standard model and PCL library.

关键词： human body model rapid modeling PCL kinect sensor anthropometric parameters

Design and Implementation of Number Gesture Recognition System Based on kinect

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Design and Implementation of Number Gesture Recognition Syst...

第三十九届中国控制会议

作者： Xingxiu He Jia Zhang School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control of Complex System

The paper designs a number gesture recognition system based on kinect. The system uses the depth image captured by kinect sensor to extract gesture information for recognition. In the process of recognition, the AdaBoost algorithm in machine learning is adopted firstly, by the help of Visual Gesture Builder to train the number gesture classifier,and export the classifiers to the recognition program to recognize the current gesture. Finally, numbers are outputted according to the recognized gesture, and the basic functions of number gesture recognition system are realized. Through the experimental verification, the recognition system has enough accuracy, and the system is suitable for various factors such as environment, personnel, etc., which has a certain practical value.

关键词： kinect sensor number gesture recognition Adaboost algorithm human-computer interaction

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机器视觉在奶牛体况评定中的应用

机器视觉在奶牛体况评定中的应用

作者：王龙东华大学

学位级别：硕士

奶牛体况评定是现代奶牛养殖生产中的日常流程之一。为了获得质量安全的奶牛制品和提高奶牛生产的效率,养殖生产过程的自动化是一条必经之路。本文利用机器视觉设计的奶牛体况评定系统对提高奶牛养殖的生产效率、保证产奶品质及改善从... 详细信息

奶牛体况评定是现代奶牛养殖生产中的日常流程之一。为了获得质量安全的奶牛制品和提高奶牛生产的效率,养殖生产过程的自动化是一条必经之路。本文利用机器视觉设计的奶牛体况评定系统对提高奶牛养殖的生产效率、保证产奶品质及改善从业者工作环境都有着重要意义。本文以奶牛体况作为研究对象,在研究总结现有理论成果的基础上,提出了以kinect sensor传感器为图像传感器的方案,完成了奶牛体况评定的方案设计,搭建了软硬件平台;利用该平台对奶牛体况进行了评定实验,实验结果表明该系统较好地符合了人工评定的结论。本文在分析了系统要求的基础上,进行了系统开发。本系统以Kincet sensor为检测手段,通过红外发射机和红外摄像头结合光编码技术,kinect设备能够直接采集被摄物体的三维信息,对三维信息进行特征提取,即可实现对奶牛体表轮廓的描述,完成对奶牛体况的评定。系统采用基于Intel(?) AtomTM处理器的嵌入式平台和Windows操作系统。以kinect采集到的深度图像作为图像分析源,以OpenCV2.3.1库为图像分析工具,运用机器视觉技术和图像处理技术,构建了一套自动化奶牛体况测评系统。该系统能够根据从3个不同角度拍摄的图像,给出奶牛的体况评分,用以取代现有的、非常耗时且误差度较大的人工评分方法,其分析结果将有助于奶牛饲养方案的拟定和调整,并可以节省大量的人力和时间,为现代化奶牛养殖业的生产和研究提供提供一定的条件。本课题通过以下几个部分进行研究工作：1.奶牛体况评定研究历史与现状。2.奶牛体型评定中关键技术。3.利用深度图像进行评定奶牛体况评定的方法与原理。4.利用深度图像进行奶牛体况评定的具体实现。5.实验结果与分析。6.总结与展望。

关键词： BCS kinect sensor 图像处理轮廓查找曲线拟合