How can i create a big BoundingBox from many small BoundingBoxes for Face Detection

I have used a pre-trained face detection model https://www.ics.uci.edu/~xzhu/face/ and i have the following results

My question is how can i get a big bounding box to extract the detected face , like this:

You can download the code and images from here: https://www.ics.uci.edu/~xzhu/face/face-release1.0-basic.zip

        % compile.m should work for Linux and Mac.
    % To Windows users:
    % If you are using a Windows machine, please use the basic convolution (fconv.cc).
    % This can be done by commenting out line 13 and uncommenting line 15 in
    % compile.m
    compile;

    % load and visualize model
    % Pre-trained model with 146 parts. Works best for faces larger than 80*80
    load face_p146_small.mat

    % % Pre-trained model with 99 parts. Works best for faces larger than 150*150
    % load face_p99.mat

    % % Pre-trained model with 1050 parts. Give best performance on localization, but very slow
    % load multipie_independent.mat

    disp('Model visualization');
    visualizemodel(model,1:13);
    disp('press any key to continue');
    pause;

    % 5 levels for each octave
    model.interval = 5;
    % set up the threshold
    model.thresh = min(-0.65, model.thresh);

    % define the mapping from view-specific mixture id to viewpoint
    if length(model.components)==13 
        posemap = 90:-15:-90;
    elseif length(model.components)==18
        posemap = [90:-15:15 0 0 0 0 0 0 -15:-15:-90];
    else
        error('Can not recognize this model');
    end

    ims = dir('images/*.jpg');
    for i = 1:length(ims),
        fprintf('testing: %d/%d\n', i, length(ims));
        im = imread(['images/' ims(i).name]);
        clf; imagesc(im); axis image; axis off; drawnow;

        tic;
        bs = detect(im, model, model.thresh);
        bs = clipboxes(im, bs);
        bs = nms_face(bs,0.3);
        dettime = toc;

        % show highest scoring one
        figure,showboxes(im, bs(1),posemap),title('Highest scoring detection');
        % show all
        %figure,showboxes(im, bs,posemap),title('All detections above the threshold');

        fprintf('Detection took %.1f seconds\n',dettime);
        disp('press any key to continue');
        pause;
        close all;
    end
    disp('done!');

I think that the cordinates of the small bounding boxes are given by:

*bs.xy = *

313 209 352 248

305 209 344 248

305 209 344 248

321 209 360 248

329 209 368 248

313 193 352 232

313 177 352 216

313 161 352 200

313 153 352 192

289 153 328 192

281 153 320 192

273 153 312 192

281 145 320 184

273 145 312 184

265 153 304 192

249 137 288 176

257 129 296 168

273 121 312 160

289 129 328 168

305 137 344 176

337 153 376 192

345 153 384 192

353 153 392 192

345 145 384 184

353 145 392 184

361 153 400 192

377 137 416 176

369 129 408 168

353 129 392 168

...

385 225 424 264

385 209 424 248

393 185 432 224

393 161 432 200

Answer 1

[Image Analyst]

I have attached a function for that.