John Sprouse
Robotics Institute
Carnegie Mellon University
Place and Time
NSH 3305
11:00 AM
Abstract
This thesis proposal addresses the problem of road scene understanding for driver warning systems in intelligent vehicles, which require a model of cars, pedestrians, the lane structure of the road, and any static obstacles on it in order to accurately predict possible dangerous situations. Previous work on using computer vision in intelligent vehicle applications stops short of holistic modeling of the entire road scene. In particular, no lane tracking systems exists which detect and track multiple lanes or integrate lane tracking with tracking of cars, pedestrians, and other relevant objects. In this thesis, we focus on the goal of holistic road scene understanding, and we propose contributions in three areas: (1) the low-level detection of road scene elements such as tarmac and painted stripes; (2) modeling and tracking of complex lane structures, and (3) the integration of lane structure tracking with car and pedestrian tracking.
Further Details
A copy of the thesis oral document can be found at
link
Thesis Committee
Takeo Kanade, Chair
Charles Thorpe
Alexei Efros
Simon Baker, Microsoft Research, Seattle
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