NDLI: Biologically motivated model for encoding multiple object motions in primate visual cortex using sequences of natural images

Content Provider	IEEE Xplore Digital Library
Author	Milanova, M.G. Elmaghraby, A.S. Wachowiak, M.P. Campilho, A.
Copyright Year	2001
Description	Author affiliation: Dept. of Comput. Eng. & Comput. Sci., Louisville Univ., KY, USA (Milanova, M.G.)
Abstract	We examine the possibility that the spatiotemporal receptive field properties of visual cortical neurons can be understood in terms of a statistically efficient strategy for encoding natural time-varying images. It is believed that the sense of object motion and velocity are also related to these fields, as objects in natural scenes are represented by a sparse set of statistically independent components, such as edges. Currently, computational models of receptive fields consider only spatial components, and thus cannot account for time-varying sensory stimuli. In this paper, a model based on independent components analysis and cellular neural networks is proposed. The paper describes an artificial neural network that attempts to accurately reconstruct its spatiotemporal input data while simultaneously reducing the statistical dependencies between its outputs, as advocated by the redundancy reduction principle. This approach extends existing models to incorporate temporal aspects of sequences of images of natural scenes.
Sponsorship	IEEE Comput. Soc
Starting Page	483
Ending Page	487
File Size	540339
Page Count	5
File Format	PDF
ISBN	0769510620
DOI	10.1109/ITCC.2001.918843
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-04-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biological information theory Biological system modeling Encoding Spatiotemporal phenomena Layout Neurons Image coding Computational modeling Independent component analysis Cellular neural networks
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Spatiotemporal-chromatic structure of natural scenes

Learning Overcomplete Spatiotemporal Bubbles from Natural Image Sequences

A Model for Encoding Multiple Object Motions and Self-Motion in Area MST of Primate Visual Cortex (1998)

A Model for Encoding Multiple Object Motions and Self-Motion in Area MST of Primate Visual Cortex (1998)

Natural target localization from activity waves in the turtle visual cortex

Motion Patterns: High-Level Representation of Natural Video Sequences

Independent component analysis of natural image sequences yields spatiotemporal filters similar to simple cells in primary visual cortex (1998).

A computational model of visual cortex receptive fields using spatio-temporal filters

Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortex (1998).

Biologically motivated model for encoding multiple object motions in primate visual cortex using sequences of natural images

Similar Documents

Spatiotemporal-chromatic structure of natural scenes

Learning Overcomplete Spatiotemporal Bubbles from Natural Image Sequences

A Model for Encoding Multiple Object Motions and Self-Motion in Area MST of Primate Visual Cortex (1998)

A Model for Encoding Multiple Object Motions and Self-Motion in Area MST of Primate Visual Cortex (1998)

Natural target localization from activity waves in the turtle visual cortex

Motion Patterns: High-Level Representation of Natural Video Sequences

Independent component analysis of natural image sequences yields spatiotemporal filters similar to simple cells in primary visual cortex (1998).

A computational model of visual cortex receptive fields using spatio-temporal filters

Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortex (1998).

Biologically motivated model for encoding multiple object motions in primate visual cortex using sequences of natural images