- 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).
- 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.
- 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.
- 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.
- 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.