This week, I accomplished successfully implementing the calibration process for head pose estimation, as well as the classification that involves head pose determining when a driver is distracted or not. The calibration code works like this: the user is instructed to look straight at the road for a period of 10 seconds, during which the algorithm calculates the angle between the nose and the x and y axis, saving all of this data. Using these values, the classification determines whether the angle the driver is looking at exceeds the range of angles calculated during calibration. The updated code was integrated into the Jetson this week. To prepare for testing the code in a vehicle, there were some issues downloading Dlib onto the Jetson. I spent a couple of days trying to figure out any issues relating to installing Dlib. They have been resolved.
My progress is on schedule. Some bugs have arisen during integrating the headpose code with the rest of the algorithms which I’m currently working on to solve. After this, the team can move forward on testing the head pose feature.
In the next week, I hope to have the testing complete, as well as the final presentation slides done.