def METHOD_NAME(gpath_list, matlab_command='selective_search', verbose=VERBOSE_SS, **kwargs):
    """
    Args:
        gpath_list (list of str): the list of image paths that need proposal candidates
    Kwargs (optional): refer to the Selective Search documentation for configuration settings
    Returns:
        iter
    """
    # Form the MATLAB script command that processes images and write to
    # temporary results file.
    temp_file, temp_filepath = tempfile.mkstemp(suffix='.mat')
    os.close(temp_file)
    gpath_str = '{%s}' % (','.join(["'{}'".format(gpath) for gpath in gpath_list]))
    matlab_command_str = "{}({}, '{}')".format(matlab_command, gpath_str, temp_filepath)
    if verbose:
        logger.info('Calling: {}'.format(matlab_command_str))
    # Execute command in MATLAB.
    bash_command = 'matlab -nojvm -r "try; %s; catch; exit; end; exit"'
    bash_str = bash_command % (matlab_command_str,)
    bash_list = shlex.split(bash_str)
    with open('/dev/null', 'w') as null:
        process_id = subprocess.Popen(bash_list, stdout=null, cwd=SCRIPT_PATH)
        process_return_code = process_id.wait()
        if process_return_code != 0:
            raise RuntimeError('Matlab selective search did not exit successfully')
    # Read the results and undo Matlab's 1-based indexing.
    boxes_list = list(scipy.io.loadmat(temp_filepath)['all_boxes'][0])
    subtractor = np.array((1, 1, 0, 0))[np.newaxis, :]
    results_list = [boxes - subtractor for boxes in boxes_list]
    if len(results_list) != len(gpath_list):
        raise ValueError('Matlab selective search did not return valid data')
    # Remove temporary file, and return.
    os.remove(temp_filepath)
    # Pack results
    results_list_ = []
    for result_list in results_list:
        result_list_ = []
        for result in result_list:
            xtl = int(np.around(result[0]))
            ytl = int(np.around(result[1]))
            xbr = int(np.around(result[2]))
            ybr = int(np.around(result[3]))
            result_dict = {
                'xtl': xtl,
                'ytl': ytl,
                'width': xbr - xtl,
                'height': ybr - ytl,
                'class': None,
                'confidence': 1.0,
            }
            result_list_.append(result_dict)
        results_list_.append(result_list_)
    results_list = zip(gpath_list, results_list_)
    return results_list