This week, we’re showing off the improvements we made to our object tracking algorithm. If you’ll recall, before, we encountered issues of it reclassifying antennas a lot, resulting in several IDs for the same antenna. Though this is something that could be addressed afterwards, by setting up an algorithm to recognize when multiple IDs correspond to the same antenna, this would be rather complex and take time to do. So instead, we focused on the object detection and tracking algorithm itself, hoping to at the very least reduce the amount of post-processing we would need to do, and here are the results:
As you can see, the algorithm now does a far better job at keeping IDs consistent. There was one period where it lost track of an antenna for some time, and as a result, assigned it a new ID, but that is more likely to be the fault of the object detection algorithm than the object tracking, and is something that can be fixed by adding more training data to that model (which is something either we or Verizon would need to do at some point regardless if this project were to ever be implemented on a large scale).
You may also notice that when the drone makes a complete loop and starts the same antennas in a second loop, that also assigns new IDs. This is something we have planned to address for a while now. If you scroll back to week 8, you’ll see the prototype interface for uploading a video, and under the ‘Description’ field, there is a drop-down with numbers. This is a field for the user to submit the number of antennas on the tower they’re examining. With this information, it should be a simple matter to have our algorithm restart the IDs back to 1 once they reach that maximum value.
Depending on the performance of our angle calculation, and how much data we need from that to get accurate results, we can also simply restrict the input video to only including a single loop of the tower.