Main Tasks

1.  Study ATLASCAR vision systems and existing lasers

Comprehend all available sensors, their localization, and all software tools who are available to be data access (ROS and already existing software modules).

2. State of the art in laser-vision pedestrian detection

Search for sensors and algorithms used, as historical pedestrian detection systems and academic/comercial solutions available. 

3. Re-parametrize last year developed pedestrian detection algorithm

Comprehend how the algorithm works and run it; modify the execution parameters so that it could be used in different conditions, turning the result more efficient and versatile.   

4. Develop application for vision and laser sensor calibration in ATLASCAR.

To be able to establish a relation through an image pixels and the correct region of targets detected by a LIDAR system, it's necessary to make a geometrics transformation between the two systems and their referentials. Saying this, an application should be created, that allows the 2D image pixels being calibrated with LIDAR data in a 3D context.

5. Combine LIDAR processed data with camera images applying the pedestrian detection algorithm "actively", in a created application.
   

This last stage is one of the main tasks and consists in merging LIDAR data with the camera image, so that it could test/verify if the object in question is definitely a pedestrian.