Vision-based driver assistance systems have great potential for preventing fatalities. This work addresses the problem of 3D monocular vehicle tracking and turn rate estimation in situations where vehicles need to be tracked along intersections and curves. To estimate the tracked vehicle's turn rate, an approach based on image feature correspondences and a simplified geometric vehicle model is used. The model is robustly and efficiently fitted to the matched image features using an improved RANSAC scheme that automatically enforces physically plausible vehicle motions and speeds up the overall system at the same time. Temporal integration of the computed turn rates is performed by an Extended Kalman Filter with the bicycle motion model. Experiments with real world data show the applicability and robustness of the proposed concepts.
Feature-based monocular vehicle turn rate estimation from a moving platform
2013-06-01
1049131 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
FEATURE-BASED MONOCULAR VEHICLE TURN RATE ESTIMATION FROM A MOVING PLATFORM
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