Custom feature extractor is not recognized by bagOfFeatures function

Hi, I'm trying to create a bag-of-visual-words model using my custom feature extractor function, but the BoW is always generated using SURF features. Below is a toy example to reproduce the problem:

clc; clear all; close all; 

% Load images in the workspace
imageDir = fullfile(toolboxdir('vision'),'visiondata','structureFromMotion');
% Create an imageDataStore object 
imds = imageDatastore(imageDir); 

% Test the feature extractor
I = readimage(imds, 1); 
[features, featureMetrics] = exampleExtractor(I); 

% Create a virtual vocabulary with the custom feature descriptor
extractor = @exampleExtractor; 
imageIndex = indexImages(imds); 
bag = bagOfFeatures(imds, 'CustomExtractor', extractor, ...
            'TreeProperties', [2, 10], 'StrongestFeatures', 1); 

function [features, featureMetrics, varargout] = exampleExtractor(I)
    % Convert image to grayscale, if necessary
    [height, width, numChannels] = size(I); 
    if numChannels > 1
        grayImage = rgb2gray(I); 
    else
        grayImage = I; 
    end
    % Define a regular grid over I
    gridStep = 8; 
    gridX = 1:gridStep:width; 
    gridY = 1:gridStep:height; 
    [X,Y] = meshgrid(gridX, gridY); 
    gridLocations = [X(:), Y(:)]; 
    % Multi-scale feature extraction
    multiscaleGridPoints = [SIFTPoints(gridLocations, 'Scale', 1.6); 
                            SIFTPoints(gridLocations, 'Scale', 3.2); 
                            SIFTPoints(gridLocations, 'Scale', 4.8)]; 
    features = extractFeatures(grayImage, multiscaleGridPoints, ...
                                'Upright', true, 'Method', 'SIFT'); 
    % Compute the feature metric
    featureMetrics = var(features, [], 2); 
    % Optinal output
    if nargout > 2
        varargout{1} = multiscaleGridPoints.Location; 
    end

end

Although the custom feature extractor uses the SIFT feature in this code, the BoW is created using the SURF features:

Creating an inverted image index using Bag-Of-Features.
-------------------------------------------------------

Creating Bag-Of-Features.
-------------------------

* Selecting feature point locations using the Detector method.
* Extracting SURF features from the selected feature point locations.
** detectSURFFeatures is used to detect key points for feature extraction.

Does anyone know where I'm doing wrong?