Face recognition in live video

I need to detect and track faces using MatLab ....I'm suing MatLab 2014a,I tried the example on the following page but gave me an error It responds with the following message :

 Undefined function 'isOpen' for input arguments of type
'vision.VideoPlayer'.

Here is the link to the page :

 https://www.mathworks.com/help/vision/examples/face-detection-and-tracking-using-live-video-acquisition.html

Any ideas ....plz help

Answer 1

[Gareth Thomas]

Does this work for you from the example? (This is the basic starting point of that demo).

VideoPlayer Class Example

%%Play a Video File
% Read video from a file and set up player object.
videoFReader = vision.VideoFileReader('viplanedeparture.mp4');
videoPlayer = vision.VideoPlayer;

Play video. Every call to the step method reads another frame.

while ~isDone(videoFReader)
   frame = step(videoFReader);
   step(videoPlayer,frame);
end

Close the file reader and video player.

release(videoFReader);
release(videoPlayer);

[omar A.alghafoor]

Hi Mathworks team .

I am having two problems distinguishing faces using (face recognition convolutional neural network)

First: How to detect the intruder.

Second: The facial recognition overlaps between one person and another in the system.

The first test on grayscale images was good recognition, but on realtime of web camera the results are incorrect, knowing that I use a camera that has accuracy: 1024x570

note : all imge are grayscale .

Where is the defect in the code?

this my code for training dataset:

clc

clearvars

close all

%% variables

trainingNumFiles = 0.8;

rng(1)

faceData = imageDatastore('AutoCapturedFaces','IncludeSubfolders',true,'LabelSource','foldernames');

% Resize the images to the input size of the net

faceData.ReadFcn = @(loc)imresize(imread(loc),[227,227]);

% read one image to get pixel size

img = readimage(faceData,1);

% splitting the testing and training data

[trainFaceData,testFaceData] = splitEachLabel(faceData, ...

trainingNumFiles,'randomize');

%% defining CNN parameters

% defining layers

layers = [imageInputLayer([size(img,1) size(img,2) 1])

%middle layers

convolution2dLayer(5,3,'Padding', 2, 'Stride',3)

reluLayer

maxPooling2dLayer(3,'Stride',3)

%final layers

fullyConnectedLayer(8)

softmaxLayer

classificationLayer()];

% options to train the network

options = trainingOptions('sgdm', ...

'MiniBatchSize', 40, ...

'InitialLearnRate', 1e-4, ...

'MaxEpochs', 25, ...

'LearnRateSchedule', 'piecewise', ...

'LearnRateDropFactor', 0.875, ...

'LearnRateDropPeriod', 12, ...

'VerboseFrequency', 5);

% training the network

convnet = trainNetwork(trainFaceData,layers,options);

%% classifying

YTest = classify(convnet,testFaceData);

TTest = testFaceData.Labels;

%% Calculate the accuracy.

accuracy = sum(YTest == TTest)/numel(TTest)

save convnet

accuracy =

0.9375

https://www.mathworks.com/matlabcentral/answers/774947-face-recognition-convolutional-neural-network?s_tid=prof_contriblnk

Answer 2

[tamim boubou]

No, it didn't work

the video file doesn't seem to be existed in my laptop