matlab 计算机视觉工具箱step含义

% Create a cascade detector object.
faceDetector = vision.CascadeObjectDetector();
% Read a video frame and run the face detector.
videoFileReader = vision.VideoFileReader(infilename);
videoFrame      = step(videoFileReader);
bbox            = step(faceDetector,videoFrame);

上面code中，第二个step会call CascadeObjectDetector.m

%CascadeObjectDetector Detect objects using the Viola-Jones algorithm
%   DETECTOR = vision.CascadeObjectDetector creates a System object
%   that detects objects using the Viola-Jones algorithm. The DETECTOR
%   is capable of detecting a variety of objects, including faces and a
%   person's upper body. The type of object to detect is controlled by
%   the ClassificationModel property. By default, the DETECTOR is
%   configured to detect faces.
%
%   …………
%
%   BBOXES = step(DETECTOR,I) performs multi-scale object detection on
%   the input image, I, and returns, BBOXES, an M-by-4 matrix defining
%   M bounding boxes containing the detected objects. Each row in
%   BBOXES is a four-element vector, [x y width height], that specifies
%   the upper left corner and size of a bounding box in pixels. When no
%   objects are detected, BBOXES is empty. I must be a grayscale or
%   truecolor (RGB) image.

如说明，bbox是1*4向量，分布表示[x y width height]，即边界框的左上角像素点坐标和边界框的size

% Create a point tracker and enable the bidirectional error constraint to
% make it more robust in the presence of noise and clutter.
pointTracker = vision.PointTracker('MaxBidirectionalError', 2);
% Initialize the tracker with the initial point locations and the initial% video frame.points = points.Location;initialize(pointTracker, points, videoFrame);

    % get the next frame
    videoFrame = step(videoFileReader);

    % Track the points. Note that some points may be lost.
    [points, isFound] = step(pointTracker , videoFrame);

上面code中，step会call PintTracker.m

%   [POINTS, POINT_VALIDITY] = step(H, I) tracks the points in the input
%   frame, I. The output POINTS contain an M-by-2 array of [x y]
%   coordinates that correspond to the new locations of the points in the
%   input frame, I. The output, POINT_VALIDITY provides an M-by-1 logical
%   array, indicating whether or not each point has been reliably tracked.
%   The input frame, I must be the same size and data type as the video
%   frames passed to the initialize method.

其实points是xx * 2数组，xx表示特征点数目，points是所有特征的的坐标

isFound是xx * 1数组，表示特征点是否有track ok。ok是1，否则为0