How to process each frame of video using for loop and concatenate the result

Hello.

I converted video to 3D image.

(180 x 144 x 84 = width x Height x frames)

I want to process each frame and concatenate the result. (M x M x frames)

If N and M have different values after the process, I want to reduce N and M to minimum values of them.

clear all
close all
%// read the video:
list = dir('*.avi')
% loop through the filenames in the list
for k = 1:length(list)
    reader = VideoReader(list(k).name);
    vid = {};
    while hasFrame(reader)
        vid{end+1} = readFrame(reader);
    end
    for i=1:25
        fIdx(i) = i; %// do it for frame 1 ~ 25
        frameGray{i} = rgb2gray(vid{fIdx(i)});
        
        
        
        data{i} = frameGray{i}';
        data{i} = double(data{i});
        opt.init_num_secants = 180;
        idx1{i} = random('unid',size(data{i}, 2), opt.init_num_secants, 1);
        idx2{i} = random('unid',size(data{i}, 2), opt.init_num_secants, 1);
        secants{i} = data{i}(:, idx1{i})-data{i}(:, idx2{i});
        D1{i} = abs(secants{i});
        numSecants = size(data{i},1);
        options.landmarks = 1:180;
        [geo{i}] = IsomapII(D1{i}, 'k', 3, options); 
        secants{i} = geo{i}/norm(geo{i},2);
    
    
         %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
        %%%%%Parameter setting
        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
        opt.outer_iterations = 1000;
    
        switch 'l-bfgs'
            case 'grad'
            opt.linear_solver = 'grad';
            opt.tau = 1e-1; % gradient step size
            opt.inner_iterations = 10;
            opt.beta1 = 1e-1; opt.beta2 = 1e-1; %penalty parameters
            opt.eta1 = 1; opt.eta2 = 1; %lagrangian update
        case 'cgs'
            opt.linear_solver = 'cgs';
            opt.linear_iterations = 10;
            opt.inner_iterations = 1;
            opt.beta1 = 1; opt.beta2 = 1; %penalty parameters
            opt.eta1 = 1.618; opt.eta2 = 1.618; %lagrangian update
        case 'l-bfgs'
            opt.linear_solver = 'l-bfgs';
            opt.linear_iterations = 3;
            opt.lbfgs_rank = 5;
            opt.inner_iterations = 1;
            opt.beta1 = 1; opt.beta2 = 1; %penalty parameters
            opt.eta1 = 1.618; opt.eta2 = 1.618; %lagrangian update
        end
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %%End parameters
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    delta = 0.3; %max-margin parameter
    funA = @(z) funA_secants_WY(z, secants{i});
    funAT = @(z) funAT_secants_WY(z, secants{i});
    b = ones(numSecants, 1);
    ticID = tic;
    [P{i}, L{i}, q{i}, Lambda{i}, w{i}] = NuMax(funA, funAT, b, delta, opt);
    toc(ticID);
    [U{i}, S{i}, V{i}] = svd(P{i});
    r{i} = rank(P{i});
    U1{i} = U{i}(:, 1:r{i});
    U1{i} = (U1{i} - min(U1{i}(:)))/(max(U1{i}(:))-min(U1{i}(:)));
    Phi_NuMax = (U{i}(:, 1:r{i})*(S{i}(1:r{i}, 1:r{i}).^(1/2)))';
    data = data{i};
    
    Y = Phi_NuMax * data;
    end
end
    X = cell2mat(Y');

[Stephen23]

Duplicate:

https://www.mathworks.com/matlabcentral/answers/513632-unable-to-perform-assignment-because-brace-indexing-is-not-supported-for-variables-of-this-type