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3D Object Recognition Using Unsupervised Feature Extraction

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83839

Gold JI, Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Intrator, N., Gold JI, Bülthoff, H., & Edelman, S. (1992). 3D Object Recognition Using Unsupervised Feature Extraction. In Advances in Neural Information Processing Systems 4 (pp. 368-377). San Mateo, CA, USA: Kaufmann.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-EDF4-A
Zusammenfassung
Intrator (1990) proposed a feature extraction method that is related to recent statistical theory (Huber, 1985; Friedman, 1987) and is based on a biologically motivated model of neuronal plasticity (Bienenstock et al., 1982). This method has been recently applied to feature extraction in the context of recognizing 3D objects from single 2D views (Intrator and Gold, 1991). Here we describe experiments designed to analyze the nature of the extracted features, and their relevance to the theory and psychophysics of object recognition.