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Context-sensitive bicycle and pedestrian detection and tracking
Contact: Paul Rybski
Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Ave
Pittsburgh, PA 15213
Project Homepage
This page last updated - August 2011.
The detection and tracking of bicycles and pedestrians is an important technology to pursue for the sake of automotive safety for both manual and autonomous cars. We are developing algorithms which fuse cameras, lidar, and radar to detect pedestrians on foot as well as on bicycles on all sides of a vehicle. In particular, we are focusing on detecting child-sized pedestrians and people that are not necessarily standing but are in other body poses that are not addressed by currently existing camera systems such as people on crutches, using walkers, or in wheelchairs. Different sensor technologies and types are being evaluated to determine their strengths and weaknesses (e.g. performance vs. cost) for the different domains. Wherever possible, contexts of the surrounding world model will be used to improve detection and tracking.