Preallocating Tracks or Parallel Processing in a Multi Object Tracking Script

I'm working on a multi-object tracking script and I'd like to get things running as fast as possible. The way the script is currently set up a new track is created in the track structure every time a new object is detected. What I'd like to do is preallocate tracks much like I'd preallocate an array so that things run quicker. I was wondering if anyone knew any code I might use to preallocate tracks, any code I might use to clear empty tracks that were unused at the end of my run and how I might modify the function below to work with a set of preallocated tracks rather than a growing number of tracks. I would greatly appreciate any help with this. Equally helpful would be some way I might be able to implement parfor in the loop provided all the centroids, bboxes, tracks and unassigned detections were unique.

%
function [tracks_Out, nextId_Out] = createNewTracks(tracks, centroids, bboxes, unassignedDetections, nextId)
    centroids = centroids(unassignedDetections, :);
    bboxes = bboxes(unassignedDetections, :);
    tracks_Out=tracks;
    nextId_Out=nextId;
      for i = 1:size(centroids, 1)
          centroid = centroids(i,:);
          bbox = bboxes(i, :);
          % Create a Kalman filter object.
          kalmanFilter = configureKalmanFilter('ConstantVelocity', ...
              centroid, [200, 50], [100, 25], 100);
          % Create a new track.
          newTrack = struct(...
              'id', nextId_Out, ...
              'bbox', bbox, ...
              'kalmanFilter', kalmanFilter, ...
              'age', 1, ...
              'totalVisibleCount', 1, ...
              'consecutiveInvisibleCount', 0);
          % Add it to the array of tracks.
          tracks_Out(end + 1) = newTrack;
          % Increment the next id.
          nextId_Out = nextId_Out + 1;
      end
  end