Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
From volumes to views: an approach to 3-D object recognition
CVGIP: Image Understanding - Special issue on directions in CAD-based vision
Statistical Approaches to Feature-Based Object Recognition
International Journal of Computer Vision
Alignment by Maximization of Mutual Information
International Journal of Computer Vision
Model-Based Localisation and Recognition of Road Vehicles
International Journal of Computer Vision
Computer Vision
Assessing the Computational Effort for Structural 3D Vehicle Recognition
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Ansichtenbasierte Erkennung von Fahrzeugen
Mustererkennung 2000, 22. DAGM-Symposium
Pose Estimation and Recognition of Ground Vehicles in Aerial Reconnaissance Imagery
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Perceptual grouping for automatic detection of man-made structures in high-resolution SAR data
Pattern Recognition Letters - Special issue: Pattern recognition in remote sensing (PRRS 2004)
An accumulating interpreter for cognitive vision production systems
Pattern Recognition and Image Analysis
An accumulating interpreter for cognitive vision production systems
Pattern Recognition and Image Analysis
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A structural knowledge-based vehicle recognition method is modified yielding a new probabilistic foundation for the decisions. The method uses a pre-calculated set of hidden line projected views of articulated polyhedral models of the vehicles. Model view structures are set into correspondence with structures composed from edge lines in the image. The correspondence space is searched utilizing a 4D Hough-type accumulator. Probabilistic models of the background and the error in the measurements of the image structures lead to likelihood estimations that are used for the decision. The likelihood is propagated along the structure of the articulated model. The system is tested on a cluttered outdoor scene. To ensure any-time performance the recognition process is implemented in a data-driven production system.