Robust vehicle categorization from aerial images by 3D-template matching and multiple classifier system

We present a robust method for vehicle categorization in aerial images. This approach relies on a multiple-classifier system that merges the answers of classifiers applied at various camera angle incidences. The single classifiers are built by matching 3D-templates to the vehicle silhouettes with a...

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Bibliographic Details
Main Authors: Le Saux, B., Sanfourche, M.
Format: Conference Proceeding
Language:English
Subjects:
Cameras
Computational modeling
Computer vision
Feature extraction
Solid modeling
Three dimensional displays
Vehicles
Online Access:Request full text
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Summary:We present a robust method for vehicle categorization in aerial images. This approach relies on a multiple-classifier system that merges the answers of classifiers applied at various camera angle incidences. The single classifiers are built by matching 3D-templates to the vehicle silhouettes with a local projection model that is compatible with the assumption of the little knowledge that we have of the viewing-condition parameters. We assess the validity of our approach on a challenging dataset of images captured in real-world conditions.
ISSN:1845-5921