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Content Provider | IEEE Xplore Digital Library |
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Author | Liang Zhao Thorpe, C. |
Copyright Year | 1998 |
Description | Author affiliation: Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA (Liang Zhao) |
Abstract | 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. |
Starting Page | 496 |
Ending Page | 501 |
File Size | 227813 |
Page Count | 6 |
File Format | |
ISBN | 0818684976 |
ISSN | 10636919 |
DOI | 10.1109/CVPR.1998.698651 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1998-06-25 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image sequences Motion estimation Motion detection Motion analysis Real time systems Vehicles Target tracking Acceleration Robustness Path planning |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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