Performance Evaluation

FP.5 : Performance Evaluation 1

This exercise is about conducting tests with the final project code, especially with regard to the Lidar part. Look for several examples where you have the impression that the Lidar-based TTC estimate is way off. Once you have found those, describe your observations and provide a sound argumentation why you think this happened.

The task is complete once several examples (2-3) have been identified and described in detail. The assertion that the TTC is off should be based on manually estimating the distance to the rear of the preceding vehicle from a top view perspective of the Lidar points.

FP.6 : Performance Evaluation 2

This last exercise is about running the different detector / descriptor combinations and looking at the differences in TTC estimation. Find out which methods perform best and also include several examples where camera-based TTC estimation is way off. As with Lidar, describe your observations again and also look into potential reasons. This is the last task in the final project.

The task is complete once all detector / descriptor combinations implemented in previous chapters have been compared with regard to the TTC estimate on a frame-by-frame basis. To facilitate the comparison, a spreadsheet and graph should be used to represent the different TTCs.

We are super-excited to receive your submission as soon as possible.