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Proceedings Paper

Model-based car tracking through the integration of search and estimation
Author(s): Hichem Sahli; Mark J. W. Mertens; Jan P.H. Cornelis
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Paper Abstract

In this work we address the problem of detecting and tracking moving vehicles in image sequences on highway scenes recorded by a moving camera. The proposed method uses a simple parameterized vehicle shape (object-model) and vehicle motion model for an intra-frame matching and a recursive estimation of position, orientation, velocity and shape parameters of the tracked vehicle. In our approach the vehicle detection/identification (matching) is tackled in an optimization framework, implemented as a hypothesis generation and testing method, in which the current set of hypotheses (vehicle shape) are evaluated and modified until a maximum cost instantiation is found. The estimation of the vehicle position, orientation and velocity is based on a ground plane motion constraint and a Kalman Filtering approach. Results on real world highway scenes are presented and open problems are discussed.

Paper Details

Date Published: 30 July 1998
PDF: 7 pages
Proc. SPIE 3364, Enhanced and Synthetic Vision 1998, (30 July 1998); doi: 10.1117/12.317465
Show Author Affiliations
Hichem Sahli, Vrije Univ. Brussel (Belgium)
Mark J. W. Mertens, Vrije Univ. Brussel (Netherlands)
Jan P.H. Cornelis, Vrije Univ. Brussel (Belgium)


Published in SPIE Proceedings Vol. 3364:
Enhanced and Synthetic Vision 1998
Jacques G. Verly, Editor(s)

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