使用 KTH 数据集进行人类行为识别（Matlab代码实现）

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📋📋📋本文目录如下：🎁🎁🎁

目录

💥1 概述

📚2 运行结果

🎉3 参考文献

🌈4 Matlab代码实现

---

💥1 概述

本文的Matlab 代码是为了使用时空兴趣点 （STIP） 识别人类行为，即“行走”、“慢跑”、“跑步”、“拳击”、“挥手”和“拍手”，并使用 KNN 分类器对其进行分类。请从链接 Dismissed site: www.nada.kth.se 下载 KTH 操作识别数据集，并将其放入文件夹 KTH 数据集文件夹中。

📚2 运行结果

部分代码：

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
                   'gui_Singleton',  gui_Singleton, ...
                   'gui_OpeningFcn', @main_OpeningFcn, ...
                   'gui_OutputFcn',  @main_OutputFcn, ...
                   'gui_LayoutFcn',  [] , ...
                   'gui_Callback',   []);
if nargin && ischar(varargin{1})
    gui_State.gui_Callback = str2func(varargin{1});
end

if nargout
    [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
else
    gui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT

% --- Executes just before main is made visible.
function main_OpeningFcn(hObject, eventdata, handles, varargin)
% This function has no output args, see OutputFcn.
% hObject    handle to figure
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
% varargin   command line arguments to main (see VARARGIN)

% Choose default command line output for main
handles.output = hObject;
ah=axes('unit','normalized','position',[0 0 1 1]);
bg=imread('Files\1.jpg'); imagesc(bg);
set(ah,'handlevisibility','off','visible','off');
uistack(ah,'bottom');
% Update handles structure
guidata(hObject, handles);

% UIWAIT makes main wait for user response (see UIRESUME)
% uiwait(handles.figure1);

% --- Outputs from this function are returned to the command line.
function varargout = main_OutputFcn(hObject, eventdata, handles) 
% varargout  cell array for returning output args (see VARARGOUT);
% hObject    handle to figure
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Get default command line output from handles structure
varargout{1} = handles.output;

% --- Executes on button press in Input.
function Input_Callback(hObject, eventdata, handles)
global vfilename;
global vpathname;
global nFrames;
global vi;
global k
delete('frames\*.jpg');
[ vfilename, vpathname ] = uigetfile( 'dataset\*.avi', 'Select an video' );
I=mmreader(strcat( vpathname, vfilename ));
nFrames = I.numberofFrames;
vidHeight =  I.Height;
vidWidth =  I.Width;
mov(1:nFrames) = ...
    struct('cdata', zeros(vidHeight, vidWidth, 3, 'uint8'),...
           'colormap', []);
for k = 1: nFrames
    mov(k).cdata = read( I, k);
   mov(k).cdata = imresize(mov(k).cdata,[256,256]);
    imwrite(mov(k).cdata,['Frames\',num2str(k),'.jpg']);
end
implay([vpathname vfilename]);
% hObject    handle to Input (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% --- Executes on button press in frameconversion.
function frameconversion_Callback(hObject, eventdata, handles)
for I = 1:50
    im=imread(['Frames\',num2str(I),'.jpg']);
    figure(1),subplot(5,10,I),imshow(im);
    axis off;
 end;
% hObject    handle to frameconversion (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

🎉3 参考文献

部分理论来源于网络，如有侵权请联系删除。

[1] Schüldt, Christian, Ivan Laptev, and Barbara Caputo. "Recognizing human actions: a local SVM approach." Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on. Vol. 3. IEEE, 2004

🌈4 Matlab代码实现