多张面孔检测与跟踪

• 环境配置
• 运行代码

  1.1    访问：Webcam Support Package。击右下角位置的download，下载Webcam安装包

1.2 需要将安装包放在matlab 的当前路径，双击 usbwebcams.mlpkginstall

1.3 点击该文件根据提示，进行安装

在安装完成结束后，在命令行输入：webcam后出现下图属性情况，则说明安装成功

运行代码

%% detectAndTrackFaces% Automatically detects and tracks multiple faces in a webcam-acquired% video stream.%% Copyright 2013-2014 The MathWorks, Inc clear classes;%% Instantiate video device, face detector, and KLT object trackervidObj = webcam;faceDetector = vision.CascadeObjectDetector(); % Finds faces by defaulttracker = MultiObjectTrackerKLT;%% Get a frame for frame-size informationframe = snapshot(vidObj);frameSize = size(frame);%% Create a video player instancevideoPlayer  = vision.VideoPlayer('Position',[200 100 fliplr(frameSize(1:2)+30)]);%% Iterate until we have successfully detected a facebboxes = [];while isempty(bboxes)    framergb = snapshot(vidObj);    frame = rgb2gray(framergb);    bboxes = faceDetector.step(frame);endtracker.addDetections(frame, bboxes);%% And loop until the player is closedframeNumber = 0;keepRunning = true;disp('Press Ctrl-C to exit...');while keepRunning    framergb = snapshot(vidObj);    frame = rgb2gray(framergb);    if mod(frameNumber, 10) == 0        % (Re)detect faces.        %        % NOTE: face detection is more expensive than imresize; we can        % speed up the implementation by reacquiring faces using a        % downsampled frame:        % bboxes = faceDetector.step(frame);        bboxes = 2 * faceDetector.step(imresize(frame, 0.5));        if ~isempty(bboxes)            tracker.addDetections(frame, bboxes);        end    else        % Track faces        tracker.track(frame);    end    % Display bounding boxes and tracked points.    displayFrame = insertObjectAnnotation(framergb, 'rectangle',...        tracker.Bboxes, tracker.BoxIds);    displayFrame = insertMarker(displayFrame, tracker.Points);    videoPlayer.step(displayFrame);    frameNumber = frameNumber + 1;end%% Clean uprelease(videoPlayer);

以下函数命名为：MultiObjectTrackerKLT.m 

classdef MultiObjectTrackerKLT < handle    properties        % PointTracker A vision.PointTracker object        PointTracker;                 % Bboxes M-by-4 matrix of [x y w h] object bounding boxes        Bboxes = [];                % BoxIds M-by-1 array containing ids associated with each bounding box        BoxIds = [];                % Points M-by-2 matrix containing tracked points from all objects        Points = [];                % PointIds M-by-1 array containing object id associated with each         %   point. This array keeps track of which point belongs to which object.        PointIds = [];                % NextId The next new object will have this id.        NextId = 1;                % BoxScores M-by-1 array. Low box score means that we probably lost the object.        BoxScores = [];    end        methods        %------------------------------------------------------------------        function this = MultiObjectTrackerKLT()        % Constructor            this.PointTracker = ...                vision.PointTracker('MaxBidirectionalError', 2);        end                %------------------------------------------------------------------        function addDetections(this, I, bboxes)        % addDetections Add detected bounding boxes.        % addDetections(tracker, I, bboxes) adds detected bounding boxes.        % tracker is the MultiObjectTrackerKLT object, I is the current        % frame, and bboxes is an M-by-4 array of [x y w h] bounding boxes.        % This method determines whether a detection belongs to an existing        % object, or whether it is a brand new object.            for i = 1:size(bboxes, 1)                % Determine if the detection belongs to one of the existing                % objects.                boxIdx = this.findMatchingBox(bboxes(i, :));                                if isempty(boxIdx)                    % This is a brand new object.                    this.Bboxes = [this.Bboxes; bboxes(i, :)];                    points = detectMinEigenFeatures(I, 'ROI', bboxes(i, :));                    points = points.Location;                    this.BoxIds(end+1) = this.NextId;                    idx = ones(size(points, 1), 1) * this.NextId;                    this.PointIds = [this.PointIds; idx];                    this.NextId = this.NextId + 1;                    this.Points = [this.Points; points];                    this.BoxScores(end+1) = 1;                                    else % The object already exists.                                        % Delete the matched box                    currentBoxScore = this.deleteBox(boxIdx);                                        % Replace with new box                    this.Bboxes = [this.Bboxes; bboxes(i, :)];                                        % Re-detect the points. This is how we replace the                    % points, which invariably get lost as we track.                    points = detectMinEigenFeatures(I, 'ROI', bboxes(i, :));                    points = points.Location;                    this.BoxIds(end+1) = boxIdx;                    idx = ones(size(points, 1), 1) * boxIdx;                    this.PointIds = [this.PointIds; idx];                    this.Points = [this.Points; points];                                        this.BoxScores(end+1) = currentBoxScore + 1;                end            end                        % Determine which objects are no longer tracked.            minBoxScore = -2;            this.BoxScores(this.BoxScores < 3) = ...                this.BoxScores(this.BoxScores < 3) - 0.5;            boxesToRemoveIds = this.BoxIds(this.BoxScores < minBoxScore);            while ~isempty(boxesToRemoveIds)                this.deleteBox(boxesToRemoveIds(1));                boxesToRemoveIds = this.BoxIds(this.BoxScores < minBoxScore);            end                        % Update the point tracker.            if this.PointTracker.isLocked()                this.PointTracker.setPoints(this.Points);            else                this.PointTracker.initialize(this.Points, I);            end        end                        %------------------------------------------------------------------        function track(this, I)        % TRACK Track the objects.        % TRACK(tracker, I) tracks the objects into frame I. tracker is the        % MultiObjectTrackerKLT object, I is the current video frame. This        % method updates the points and the object bounding boxes.            [newPoints, isFound] = this.PointTracker.step(I);            this.Points = newPoints(isFound, :);            this.PointIds = this.PointIds(isFound);            generateNewBoxes(this);            if ~isempty(this.Points)                this.PointTracker.setPoints(this.Points);            end        end    end        methods(Access=private)                %------------------------------------------------------------------        function boxIdx = findMatchingBox(this, box)        % Determine which tracked object (if any) the new detection belongs to.             boxIdx = [];            for i = 1:size(this.Bboxes, 1)                area = rectint(this.Bboxes(i,:), box);                                if area > 0.2 * this.Bboxes(i, 3) * this.Bboxes(i, 4)                     boxIdx = this.BoxIds(i);                    return;                end            end                   end                %------------------------------------------------------------------        function currentScore = deleteBox(this, boxIdx)                    % Delete object.            this.Bboxes(this.BoxIds == boxIdx, :) = [];            this.Points(this.PointIds == boxIdx, :) = [];            this.PointIds(this.PointIds == boxIdx) = [];            currentScore = this.BoxScores(this.BoxIds == boxIdx);            this.BoxScores(this.BoxIds == boxIdx) = [];            this.BoxIds(this.BoxIds == boxIdx) = [];                    end                %------------------------------------------------------------------        function generateNewBoxes(this)          % Get bounding boxes for each object from tracked points.            oldBoxIds = this.BoxIds;            oldScores = this.BoxScores;            this.BoxIds = unique(this.PointIds);            numBoxes = numel(this.BoxIds);            this.Bboxes = zeros(numBoxes, 4);            this.BoxScores = zeros(numBoxes, 1);            for i = 1:numBoxes                points = this.Points(this.PointIds == this.BoxIds(i), :);                newBox = getBoundingBox(points);                this.Bboxes(i, :) = newBox;                this.BoxScores(i) =���,��Ŀ oldScores(oldBoxIds == this.BoxIds(i));            end        end     endend%--------------------------------------------------------------------------function bbox = getBoundingBox(points)x1 = min(points(:, 1));y1 = min(points(:, 2));x2 = max(points(:, 1));y2 = max(points(:, 2));bbox = [x1 y1 x2 - x1 y2 - y1];end

运行效果图（因为是夜晚，只有我一人检测，所有没有多目标检测）