NDLI: Fast and robust prediction of optical flow field sequences for visuomotor anticipation

Content Provider	IEEE Xplore Digital Library
Author	Stephan, V. Winkler, T. Gross, H.-M.
Copyright Year	2000
Description	Author affiliation: Dept. of Neuroinf., Tech. Univ. Ilmenau, Germany (Stephan, V.)
Abstract	In this paper, we present a hybrid neural architecture to predict optical flow fields as consequences of real and hypothetical actions. In this architecture, we introduce a neural field-based method to fuse sensory bottom-up and predicted top-down expectations. All subsystems extensively use confidence estimations to reduce disturbances caused by noise. The facilities of this anticipative preprocessing can be demonstrated by means of an optical flow field based local navigation behavior of the miniature robot KHEPERA. Our anticipative preprocessing enables the robot to bridge gaps of sensory dropouts and, in consequence, to avoid collisions even with very noisy sensory information.
Starting Page	436
Ending Page	441
File Size	695618
Page Count	6
File Format	PDF
ISBN	0769506194
ISSN	10987576
DOI	10.1109/IJCNN.2000.861508
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-07-27
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Image motion analysis Optical sensors Optical noise Robot sensing systems Fusion power generation Fuses Noise reduction Navigation Predictive models
Content Type	Text
Resource Type	Article

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Fast and robust prediction of optical flow field sequences for visuomotor anticipation