【行为识别】基于matlab差影法三维人体姿态行为识别【含Matlab源码277期】

【⾏为识别】基于matlab差影法三维⼈体姿态⾏为识别【含Matlab源码277期】⼀、简介

该课题为基于MATLAB差影法的⼈体姿态识别。需要准备对应的模板图⽚作为背景图，然后测试图和背景图进⾏作差，结合形态学知识，提取出⼈体轮廓，接上最外接矩形，得出矩形长宽，计算长宽⽐例，从⽽判断⼈体姿态。优点是通俗易懂，缺点是局限性⼤，因为对背景图⽚要求⽐较⾼。另外可改造成不需要模板图⽚的纯形态学或者利⽤帧差法识别的基于视频的⼈体⾏为检测。

⼆、部分源代码

%[X, R, t]= function recon3DPose(xy,im,varargin)

% Inputs: xy -[2 x 14] matrix of 2D joint locations

% im - Input image

% Outputs: X -[3 x 14] matrix of 3D joint locations.

% R -[3 x 3] Relative Camera Rotation.

% t -[3 x 1] Relative Camera translation.

% Wrapper for reconstruction of the 3D Pose of a human figure given the

% locations of the 2D anatomical landmarks.

% This program is free software: you can redistribute it and/or modify

% it under the terms of the GNU General Public License as published by

% the Free Software Foundation, either version 3 of the License, or

%(at your option) any later version.

% This program is distributed in the hope that it will be useful,

% but WITHOUT ANY WARRANTY; without even the implied warranty of

% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the

% GNU General Public License for more details.

% You should have received a copy of the GNU General Public License

微型超级电容器% along with this program. If not, see </licenses/>.

function [X, R, t]=recon3DPose(im,xy,varargin)

%[X, R, t]=recon3DPose(xy,im,varargin)

% Parse parameters.

[pose.skel, pose.BOMP, pose.mu, pose.lambda1,...

pose.lamda2, pose.K, pose.numIter,...

pose.numIters2, l1, l2, pose.ks,...

pose.optType, pose.viz, pose.annoids,pose.numPoints]=process_options(varargin,...

'skel','',...

'BOMP','',...

'mu','',...

'lambda2',0.01,...

'lambda1',0.01,...

'K',setK(size(im,2),size(im,1),2),...

'numIter',20,...

'numIters2',30,...

'tol1',500,...

'tol2',1,...

'ks',15,...

'optType',1,...

'viz',0,...

'annoids',1:15,...

'numPoints',15);

pose.im = im;

< =[xy;ones(1,size(xy,2))];

% Load default basis and skeleton

if(isempty(pose.BOMP)||isempty(pose.mu)||isempty(pose.skel))

basis =load('mocapReducedModel.mat');

pose.BOMP = basis.B;

pose.mu = basis.mu;

吸湿剂pose.skel = basis.skel;

pose.numPoints =length();

电子元件打标机

pose.annoids =[1:length()];

end

% Reconstruct camera and pose.

[camera, pose]=cameraAndPose(pose);

弯头制作% Assign outputs

X = pose.XnewR;

R = camera.R;

t = camera.t;

% Show aligned output

if(pose.viz)

load frontCam;

Xnew1 =alignToCamera(pose.XnewR,camera.R,camera.t,R,t);

表面耐磨涂层

figure(9);clf;

visualizeGaussianModel(Xnew1,pose.skel);

drawCam(R,t);

end

三、运⾏结果

四、matlab版本及参考⽂献

1 matlab版本

2014a

2 参考⽂献

[1] 蔡利梅.MATLAB图像处理——理论、算法与实例分析[M].清华⼤学出版社，2020.

[2]杨丹，赵海滨，龙哲.MATLAB图像处理实例详解[M].清华⼤学出版社，2013.

[3]周品.MATLAB图像处理与图形⽤户界⾯设计[M].清华⼤学出版社，2013.

[4]刘成龙.精通MATLAB图像处理[M].清华⼤学出版社，2015.配煤

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