NDLI: A Novel Self-Organizing Neural Network for Motion Segmentation

Content Provider	Springer Nature Link
Author	Cirrincione, Giansalvo Cirrincione, Maurizio
Copyright Year	2003
Abstract	Many computer vision techniques, above all for structure from motion problems, require a segmentation of the images captured by one or more cameras. This paper deals with the segmentation based on the motion information, but can be easily extended to other cases (color, texture and so on). A new neural network, the EXIN Segmentation Neural Network (EXIN SNN) is here introduced. It is incremental, self-organizing and considers its task as the solution of a pattern recognition problem. This original approach overcomes the limits of the traditional segmentation techniques, namely the need of a spatial support for the image objects and the translation parallel to the image plane for the objects in the scene. Examples are given both for synthetic and real images.
Starting Page	27
Ending Page	35
Page Count	9
File Format	PDF
ISSN	0924669X
Journal	Applied Intelligence
Volume Number	18
Issue Number	1
e-ISSN	15737497
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2003-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial Intelligence (incl. Robotics) Mechanical Engineering Manufacturing, Machines, Tools
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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A Novel Self-Organizing Neural Network for Motion Segmentation