- Successful implementation of the Multivariable Segmentation
- Representation on the rviz platform of the Segmentation methods proposed, as it is shown on the figure below:
- Simple segmentation
- Multivariable Segmentation
- Dietmayer Segmentation
- Adaptative Breakpoint Detector
The next step, is to compare these results with a "groundtruth" and check the errors given by each method when the "threshold" values varies.
So, a "groundtruth" to make the comparison between the methods is needed.
For that I use a Matlab program made by my Co-Supervisor Jorge Almeida, this program reads the laser scans data form a .txt file, then the data is converted into Cartesian coordinates and creates a structure composed by the coordinates and a label. Then we preform the hand labeling of the data to obtain the target "groundtruth".
The data was collected during a ride to a big roundabout nearby Aveiro. In order to help the hand labeling of the laser data, I use some images took by the car's cameras.
In 1220 scans (iterations) I identified 17 moving cars and 1 bike.
Meanwhile, I've already started to think in the next phase of the project which is "Feature Extraction Algorithms". So i made a research of some state of art feature extraction algorithms and I've started to implement the algorithm developed by Kai O. Arras in "Using Boosted Features for the Detection of People in 2D Range Data", University of Freiburg.