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Proceedings Paper

Dealing with uncertain feature assessments in interactive object recognition
Author(s): Alexander Bauer; Verena Jürgens; Susanne Angele
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Paper Abstract

Object recognition is a typical task of aerial reconnaissance and especially in military applications, to determine the class of an unknown object on the battlefield can give valuable information on its capabilities and its threat. RecceMan® (Reconnaissance Manual) is a decision support system for object recognition developed by the Fraunhofer IOSB. It supports object recognition by automating the tedious task of matching the object features with the set of possible object classes, while leaving the assessment of features to the trained human interpreter. The quality of the features assessed by the user is influenced by several factors such as the quality of the image of the object. These factors are potential sources of error, which can lead to an incorrect classification and therefore have to be considered by the system. To address this issue, two methods for consideration of uncertainty in human feature assessment - a probabilistic and a heuristic approach - are presented and compared based on an experiment in the exemplary domain of flower recognition.

Paper Details

Date Published: 11 October 2010
PDF: 7 pages
Proc. SPIE 7835, Electro-Optical Remote Sensing, Photonic Technologies, and Applications IV, 78350L (11 October 2010); doi: 10.1117/12.865043
Show Author Affiliations
Alexander Bauer, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Verena Jürgens, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Susanne Angele, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)


Published in SPIE Proceedings Vol. 7835:
Electro-Optical Remote Sensing, Photonic Technologies, and Applications IV
Gary W. Kamerman; Gary J. Bishop; John D. Gonglewski; Ove Steinvall; Keith L. Lewis; Richard C. Hollins; Thomas J. Merlet, Editor(s)

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