Phase-Based Binocular Perception of Motion in Depth: Cortical-Like Operators and Analog VLSI Architectures

We present a cortical-like strategy to obtain reliable estimates of the motions of objects in a scene toward/away from the observer (motion in depth), from local measurements of binocular parameters derived from direct comparison of the results of monocular spatiotemporal filtering operations perfor...

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Main Authors: Silvio P. Sabatini, Fabio Solari, Paolo Cavalleri, Giacomo Mario Bisio
Format: Article
Language:English
Published: SpringerOpen 2003-06-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://dx.doi.org/10.1155/S1110865703302033
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spelling doaj-373a7938e46942cc937892b73757f1e62020-11-25T01:00:13ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802003-06-012003769070210.1155/S1687617203302033Phase-Based Binocular Perception of Motion in Depth: Cortical-Like Operators and Analog VLSI ArchitecturesSilvio P. SabatiniFabio SolariPaolo CavalleriGiacomo Mario BisioWe present a cortical-like strategy to obtain reliable estimates of the motions of objects in a scene toward/away from the observer (motion in depth), from local measurements of binocular parameters derived from direct comparison of the results of monocular spatiotemporal filtering operations performed on stereo image pairs. This approach is suitable for a hardware implementation, in which such parameters can be gained via a feedforward computation (i.e., collection, comparison, and punctual operations) on the outputs of the nodes of recurrent VLSI lattice networks, performing local computations. These networks act as efficient computational structures for embedded analog filtering operations in smart vision sensors. Extensive simulations on both synthetic and real-world image sequences prove the validity of the approach that allows to gain high-level information about the 3D structure of the scene, directly from sensorial data, without resorting to explicit scene reconstruction.http://dx.doi.org/10.1155/S1110865703302033cortical architecturesphase-based dynamic stereoscopymotion processingGabor filterslattice networks.
collection DOAJ
language English
format Article
sources DOAJ
author Silvio P. Sabatini
Fabio Solari
Paolo Cavalleri
Giacomo Mario Bisio
spellingShingle Silvio P. Sabatini
Fabio Solari
Paolo Cavalleri
Giacomo Mario Bisio
Phase-Based Binocular Perception of Motion in Depth: Cortical-Like Operators and Analog VLSI Architectures
EURASIP Journal on Advances in Signal Processing
cortical architectures
phase-based dynamic stereoscopy
motion processing
Gabor filters
lattice networks.
author_facet Silvio P. Sabatini
Fabio Solari
Paolo Cavalleri
Giacomo Mario Bisio
author_sort Silvio P. Sabatini
title Phase-Based Binocular Perception of Motion in Depth: Cortical-Like Operators and Analog VLSI Architectures
title_short Phase-Based Binocular Perception of Motion in Depth: Cortical-Like Operators and Analog VLSI Architectures
title_full Phase-Based Binocular Perception of Motion in Depth: Cortical-Like Operators and Analog VLSI Architectures
title_fullStr Phase-Based Binocular Perception of Motion in Depth: Cortical-Like Operators and Analog VLSI Architectures
title_full_unstemmed Phase-Based Binocular Perception of Motion in Depth: Cortical-Like Operators and Analog VLSI Architectures
title_sort phase-based binocular perception of motion in depth: cortical-like operators and analog vlsi architectures
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2003-06-01
description We present a cortical-like strategy to obtain reliable estimates of the motions of objects in a scene toward/away from the observer (motion in depth), from local measurements of binocular parameters derived from direct comparison of the results of monocular spatiotemporal filtering operations performed on stereo image pairs. This approach is suitable for a hardware implementation, in which such parameters can be gained via a feedforward computation (i.e., collection, comparison, and punctual operations) on the outputs of the nodes of recurrent VLSI lattice networks, performing local computations. These networks act as efficient computational structures for embedded analog filtering operations in smart vision sensors. Extensive simulations on both synthetic and real-world image sequences prove the validity of the approach that allows to gain high-level information about the 3D structure of the scene, directly from sensorial data, without resorting to explicit scene reconstruction.
topic cortical architectures
phase-based dynamic stereoscopy
motion processing
Gabor filters
lattice networks.
url http://dx.doi.org/10.1155/S1110865703302033
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AT paolocavalleri phasebasedbinocularperceptionofmotionindepthcorticallikeoperatorsandanalogvlsiarchitectures
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