Title :
Feature-based monocular vehicle turn rate estimation from a moving platform
Author :
Gabb, Michael ; Kaliuk, Artem ; Ruland, Thomas ; Lohlein, Otto ; Westenberger, Antje ; Dietmayer, Klaus
Author_Institution :
Dept. of Meas., Control & Microtechnol., Univ. of Ulm, Ulm, Germany
Abstract :
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.
Keywords :
Kalman filters; computer vision; driver information systems; feature extraction; image matching; iterative methods; nonlinear filters; object tracking; 3D monocular vehicle tracking; bicycle motion model; extended Kalman filter; feature-based monocular vehicle turn rate estimation; image feature correspondences; image matching; improved RANSAC scheme; moving platform; plausible vehicle motions; random sample consensus; simplified geometric vehicle model; temporal integration; vision-based driver assistance systems; Cameras; Estimation; Feature extraction; Robustness; Solids; Tracking; Vehicles;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2013 IEEE
Conference_Location :
Gold Coast, QLD
Print_ISBN :
978-1-4673-2754-1
DOI :
10.1109/IVS.2013.6629539