【作者】 汪丹桂；

【导师】 罗斌；

【作者基本信息】 安徽大学 ， 计算机应用， 2010， 硕士

【摘要】 步态识别技术是通过研究步态图像序列中人的行走方式来识别个体的一种技术,因其可以远距离识别,具有不可侵犯性,被广泛应用在视频监控领域,近年来成为生物特征识别领域的研究热点之一。本文在步态轮廓检测,步态特征提取和步态识别方面做了以下工作：在步态检测方面,利用自适应高斯混合模型进行背景建模,利用背景减除法提取出步态轮廓后进行滤波处理,并与帧差法提取运动目标进行对比,实验结果表明利用背景建模法建立背景后,背景减除法提取的运动目标轮廓较准确。在阴影检测方面,利用阴影的视觉特性来判断是否存在阴影,对存在的阴影利用多梯度分析和二值快速聚类法检测,将其与一般的检测方法进行对比,可知二值快速聚类法的检测效果较好。在步态特征提取方面,分别提取步态的动态特征和静态特征,基于步态轮廓提取一个步态周期内的步态宽度特征和步态轮廓直方图特征,再利用傅里叶变换和小波变换的基础理论,提取步态轮廓的傅里叶描述子特征和小波矩特征,根据特征数据分布的不同,对高维特征向量分别利用不同的降维算法,例如PCA+LDA算法,LPP算法等,将高维特征降为低维特征,减少后续识别的运算量。在步态识别方面,分别利用隐式马尔科夫模型进行步态识别和利用模糊积分对分类器进行融合识别,并将识别结果进行比较。模糊积分融合方法是根据不同特征的识别率来确定分类器的隶属度,根据隶属矩阵来确定分类器的重要性,能够更好的使分类器之间互补,从而能将步态特征在决策层进行有效的融合。最后,利用VC调用MATLAB引擎进行步态运动目标的提取,使用中科院步态数据库20个人3个视角的步态视频进行仿真实验,证明本文所采用的方法具有优越性。更多还原

【Abstract】 Gait recognition is a technology which detected the gait through a series of video gait images sequences. Since it can detect the object from a long distance and could not be offensive, so it is widely used in the area of video surveillance.In this thesis, the following work about gait detection、feature extraction and gait recognition is done:In the area of gait recognition, the adaptive Gaussian mixture model is used to construct the background model. Background reduction division is also used to extract the gait contour. The experiment results show the method in this thesis is much better compared to the frame difference method.In the process of shadow detection the existence of the shadow is judged based on the visual characteristics of shadows. If the shadow exists, gradient analysis and binary fast clustering method are used to detect it. At last the two methods are compared with each other and the result can prove the binary fast clustering method is better.In gait characteristics extraction, dynamic characteristic gait and static characteristics were extracted based on the Gait contour. The gait width characteristics and the gait outline histogram, Fourier descriptor features and characteristics of wavelet using the Fourier transform and basic theory of wavelet transform in a gait circle are extracted.And PCA together with LDA is used to reduce the feature’s dimension. LLE and LPP are also introduced. The work can reduce the complex of the following recognition.In gait feature recognition, fuzzy integral is used in classifiers fusion, the classifier’s importance is determined according to the characteristics of the subordinate matrix after the membership is determined. Thus make classifier is complementary, can be effectively in decision-making compared to the HMM model method.Lastly, use VC calls MATLAB engine to get the gait moving targets, use Gait database of 20 individual with three perspectives of video gait sequence to construct the simulation experiment, the experiment result in this thesis proves the method has advantages. Key words:Fuzzy Integral; Moving Object Detection; Moving Shadow Detection; Background Modeling; Gait Recognition更多还原