First investigations on detection of stationary vehicles in airborne decimeter resolution SAR data by supervised learning

Oliver Maksymiuk, Michael Schmitt, Andreas R. Brenner, Uwe Stilla

Publikation: KonferenzbeitragPapierBegutachtung

6 Zitate (Scopus)

Abstract

In this work we investigate the automatic detection of stationary vehicles in SAR images by supervised learning algorithms. This implies the description of the vehicles by a set of representative features. We combine several classes of features including subspace projection based on clustering mechanisms (NMF, PCA), statistical features (image moments), spectral features (gabor wavelets) as well as boundary (shape analysis) and region descriptors (HOG). We further use two different learning algorithms: Support Vector Machines (SVM) and Random Forests.

OriginalspracheEnglisch
Seiten3584-3587
Seitenumfang4
DOIs
PublikationsstatusVeröffentlicht - 2012
Veranstaltung2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Deutschland
Dauer: 22 Juli 201227 Juli 2012

Konferenz

Konferenz2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
Land/GebietDeutschland
OrtMunich
Zeitraum22/07/1227/07/12

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