Qualitative detection of motion by a moving observer
International Journal of Computer Vision
Surface correspondence and motion computation from a pair of range images
Computer Vision and Image Understanding
Interactive Model-Based Vehicle Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Active Recovery of 3D Motion Trajectories and Their Use in Prediction
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Real-time Computer Vision System for Measuring Traffic Parameters
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Derivation of qualitative information in motion analysis
Image and Vision Computing
Visual Surveillance for Moving Vehicles
International Journal of Computer Vision - Special issue on a special section on visual surveillance
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Clipped input RLS applied to vehicle tracking
EURASIP Journal on Applied Signal Processing
Model based vehicle detection and tracking for autonomous urban driving
Autonomous Robots
Laser-based detection and tracking moving objects using data-driven Markov chain Monte Carlo
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Multiclass Multimodal Detection and Tracking in Urban Environments
International Journal of Robotics Research
Integrating the projective transform with particle filtering for visual tracking
Journal on Image and Video Processing - Special issue on advanced video-based surveillance
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In this paper, we present a car tracking system which provides quantitative and qualitative motion estimates of the tracked car simultaneously from a moving observer. First, we construct three motion models (constant velocity, constant acceleration, and turning) to describe the qualitative motion of a moving car. Then the models are incorporated into the Extended Kalman Filters to perform quantitative tracking. Finally, we develop an Extended Interacting Multiple Model (EIMM) algorithm to manage the switching between models and to output both qualitative and quantitative motion estimates of the tracked car. Accurate motion modeling and efficient model management result in a high performance tracking system. The experimental results on simulated and real data demonstrate that our tracking system is reliable and robust, and runs in real-time. The multiple motion representations make the system useful in various autonomous driving tasks.