how would i track the speed of the centroid of the moving objects?

function multiObjectTracking()
obj = setupSystemObjects();
tracks = initializeTracks(); % Create an empty array of tracks.
nextId = 1; % ID of the next track
while ~isDone(obj.reader)
    frame = readFrame();
    [centroids, bboxes, mask] = detectObjects(frame);
    predictNewLocationsOfTracks();
    [assignments, unassignedTracks, unassignedDetections] = ...
        detectionToTrackAssignment();
    updateAssignedTracks();
    updateUnassignedTracks();
    deleteLostTracks();
    createNewTracks();
    displayTrackingResults();
end
function obj = setupSystemObjects()
        obj.reader = vision.VideoFileReader('YourAVI.avi');
        obj.videoPlayer = vision.VideoPlayer('Position', [20, 400, 700, 400]);
        obj.maskPlayer = vision.VideoPlayer('Position', [740, 400, 700, 400]);
        obj.detector = vision.ForegroundDetector('NumGaussians', 3, ...
            'NumTrainingFrames', 40, 'MinimumBackgroundRatio', 0.7);
        obj.blobAnalyser = vision.BlobAnalysis('BoundingBoxOutputPort', true, ...
            'AreaOutputPort', true, 'CentroidOutputPort', true, ...
            'MinimumBlobArea', 400);
end
function tracks = initializeTracks()
        tracks = struct(...
            'id', {}, ...
            'bbox', {}, ...
            'kalmanFilter', {}, ...
            'age', {}, ...
            'totalVisibleCount', {}, ...
            'consecutiveInvisibleCount', {});
    end
function frame = readFrame()
        frame = obj.reader.step();

      end
  function [centroids, bboxes, mask] = detectObjects(frame)
          mask = obj.detector.step(frame);
          mask = imopen(mask, strel('rectangle', [3,3]));
          mask = imclose(mask, strel('rectangle', [15, 15]));
          mask = imfill(mask, 'holes');
         [~, centroids, bboxes] = obj.blobAnalyser.step(mask);
      end
  function predictNewLocationsOfTracks()
          for i = 1:length(tracks)
              bbox = tracks(i).bbox;
              predictedCentroid = predict(tracks(i).kalmanFilter);
              predictedCentroid = int32(predictedCentroid) - bbox(3:4) / 2;
              tracks(i).bbox = [predictedCentroid, bbox(3:4)];
          end
  end

function [assignments, unassignedTracks, unassignedDetections] = ...
            detectionToTrackAssignment()
        nTracks = length(tracks);
        nDetections = size(centroids, 1);
        cost = zeros(nTracks, nDetections);
        for i = 1:nTracks
            cost(i, :) = distance(tracks(i).kalmanFilter, centroids);
        end
        costOfNonAssignment = 20;
        [assignments, unassignedTracks, unassignedDetections] = ...
            assignDetectionsToTracks(cost, costOfNonAssignment);
    end
 function updateAssignedTracks()
        numAssignedTracks = size(assignments, 1);
        for i = 1:numAssignedTracks
            trackIdx = assignments(i, 1);
            detectionIdx = assignments(i, 2);
            centroid = centroids(detectionIdx, :);
            bbox = bboxes(detectionIdx, :);
            correct(tracks(trackIdx).kalmanFilter, centroid);
            tracks(trackIdx).bbox = bbox;
            tracks(trackIdx).age = tracks(trackIdx).age + 1;
            tracks(trackIdx).totalVisibleCount = ...
                tracks(trackIdx).totalVisibleCount + 1;
            tracks(trackIdx).consecutiveInvisibleCount = 0;
        end
    end
   function updateUnassignedTracks()
        for i = 1:length(unassignedTracks)
            ind = unassignedTracks(i);
            tracks(ind).age = tracks(ind).age + 1;
            tracks(ind).consecutiveInvisibleCount = ...
                tracks(ind).consecutiveInvisibleCount + 1;
        end
    end
function deleteLostTracks()
        if isempty(tracks)
            return;
        end
        invisibleForTooLong = 20;
        ageThreshold = 8;
        ages = [tracks(:).age];
        totalVisibleCounts = [tracks(:).totalVisibleCount];
        visibility = totalVisibleCounts ./ ages;
        lostInds = (ages < ageThreshold & visibility < 0.6) | ...
            [tracks(:).consecutiveInvisibleCount] >= invisibleForTooLong;
        tracks = tracks(~lostInds);
    end
 function createNewTracks()
        centroids = centroids(unassignedDetections, :);
        bboxes = bboxes(unassignedDetections, :);
        for i = 1:size(centroids, 1)
            centroid = centroids(i,:);
            bbox = bboxes(i, :);
            kalmanFilter = configureKalmanFilter('ConstantVelocity', ...
                centroid, [200, 50], [100, 25], 100);
            newTrack = struct(...
                'id', nextId, ...
                'bbox', bbox, ...
                'kalmanFilter', kalmanFilter, ...
                'age', 1, ...
                'totalVisibleCount', 1, ...
                'consecutiveInvisibleCount', 0);
            tracks(end + 1) = newTrack;
            nextId = nextId + 1;
        end
 end
 function displayTrackingResults()
        frame = im2uint8(frame);
        mask = uint8(repmat(mask, [1, 1, 3])) .* 255;
        minVisibleCount = 8;
        if ~isempty(tracks)
            reliableTrackInds = ...
                [tracks(:).totalVisibleCount] > minVisibleCount;
            reliableTracks = tracks(reliableTrackInds);
            if ~isempty(reliableTracks)
                bboxes = cat(1, reliableTracks.bbox);
                ids = int32([reliableTracks(:).id]);
                labels = cellstr(int2str(ids'));
                predictedTrackInds = ...
                    [reliableTracks(:).consecutiveInvisibleCount] > 0;
                isPredicted = cell(size(labels));
                isPredicted(predictedTrackInds) = {' predicted'};
                labels = strcat(labels, isPredicted);
                frame = insertObjectAnnotation(frame, 'rectangle', ...
                    bboxes, labels);
                mask = insertObjectAnnotation(mask, 'rectangle', ...
                    bboxes, labels);
            end
        end

          obj.maskPlayer.step(mask);
          obj.videoPlayer.step(frame);
   end
  end

[Image Analyst]

I like how you're using descriptive variable names. But I'm not really sure of the question. I didn't go over it line-by-line or run it, but what's wrong with all that code you have?

[Benjamin Dempsey]

i'm wanting to track the speed of the moving objects that the code detects, thanks in advance

[Benjamin Dempsey]

I have seen your tutorials on image processing where you plot the coins positions but im not sure how i could fit that into my code

[Matthew Eicholtz]

Just to be clear, this is not your code, correct? It is the MATLAB Example for Motion-Based Multiple Object Tracking?

Answer 1

[Matthew Eicholtz]

If it is acceptable to compute velocities post hoc, I suggest the following edits to this code:

1. Add tracks as an output so you can process them from another script afterwards:

function tracks = multiObjectTracking()
...

2. In the initializeTracks() function, add a field in the tracks structure to store position over time (I suggest using an animatedline object). Also add a field to keep track of which tracks are active or not:

tracks = struct(...
    ...
    'active',{}, ...
    'position',{});

3. In the createNewTracks() function, instantiate an animated line when you create a new track and set the track to active:

newTrack = struct(...
    ...
    'active',true, ...
    'position',animatedline()); %you can add optional parameters to the animatedline here if you want

4. In the deleteLostTracks() function, instead of deleting tracks, simply set them to inactive:

Replace

lostInds = ...;
tracks = tracks(~lostInds);

with

lostInds = find(...);
for ii=1:length(lostInds)
    tracks(lostInds(ii)).active = false;
end

5. In the displayTrackingResults() function, add a condition to the reliableTrackInds to check active state:

reliableTrackInds = ... & [tracks(:).active];

Then, add the centroid location to the animatedline object for each active track (I suggest after "mask = insertObjectAnnotation..."):

x = double(bboxes(:,1)+bboxes(:,3)/2);
y = double(bboxes(:,2)+bboxes(:,4)/2);
for ii=1:length(reliableTracks)
    addpoints(tracks(reliableTracks(ii).id).position,x(ii),y(ii));
end

6. The last step is to make sure the function predictNewLocationsOfTracks(), detectionToTrackAssignment(), updateAssignedTracks(), and updateUnassignedTracks() ignore the inactive tracks. There are many potential ways to do this; I'll leave this part to you.

7. After the code has been edited, you should be able to run:

tracks = multiObjectTracking();
[x,y] = getpoints(tracks(4).position);

to get the centroid path for the 4th track, for example. The velocity can be computed easily enough with this information.

Hope this helps.

[George Kouskoulis]

Matt, I do not know for Benjamin, but this helps me a lot!

If I understand this correctly, [x, y] is not the position of the centroid in the ground but the position of the centroid in the picture of each frame (e.g. [300, 100] is the specific pixel in the picture and not a point in the ground).

How could I transform pixel's position, that comes out from your code, to position on the ground of the specific centroid, in order to compute the velocity?

Thank you in advance

[George Kouskoulis]

The conversion from pixel coordinates to ground coordinates could be done through camera calibration? Is there any other way?

Expect from the checkerboard method, how can I calibrate camera? My video covers a large area and I cannot find I huge checkerboard in order to place it the video area and do the camera calibration?

Answer 2

[George Kouskoulis]

Matt, I do not know for Benjamin, but this helps me a lot!

If I understand this correctly, [x, y] is not the position of the centroid in the ground but the position of the centroid in the picture of each frame (e.g. [300, 100] is the specific pixel in the picture and not a point in the ground).

How could I transform pixel's position, that comes out from your code, to position on the ground of the specific centroid, in order to compute the velocity?

Thank you in advance!

Answer 3

[Felix Parker]

Please let me know how to do the sixth step

[Andreas Felsing]

Doses anyone have a solution how to solve the 6th step?

Answer 4

[olivia safitri]

Doses anyone have a solution how to solve the 6th step?