title: Clustering time events
body: <p>I have a question about performing clustering with clouds of points in which one dimension - representing time - is somewhat protected.</p>
  
  <p>To make it super clear, consider this video</p>
  
  <p><img src="https://i.stack.imgur.com/ev6Ke.gif" alt="cloud_of_points"></p>
  
  <p>With a naked eye one may see some dense clouds flying around like mosquitoes, they may represent several things entering and leaving a scene. Now suppose we have an array of 3-dimensional points (x,y,time) and apply some naive clustering (say DBSCAN)</p>
  
  <p><img src="https://i.stack.imgur.com/wEWD1.gif" alt="clustering"></p>
  
  <p>Now the clustering is quite good, except that meeting events are considered in the same cluster, coming up with X-trajectories. Now if there was some way to treat the third coordinate differently, perhaps one may recover the ground truth. Which algorithms may be well suited for this problem?</p>