Vector Disparity Sensor with Vergence Control for Active Vision Systems

This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation wit...

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Main Authors: Eduardo Ros, Francisco Barranco, Javier Diaz, Silvio P. Sabatini, Agostino Gibaldi
Format: Article
Language:English
Published: MDPI AG 2012-02-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/12/2/1771/
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spelling doaj-9dd7d06e9dba4602add5fa48b0b2bee12020-11-25T01:42:32ZengMDPI AGSensors1424-82202012-02-011221771179910.3390/s120201771Vector Disparity Sensor with Vergence Control for Active Vision SystemsEduardo RosFrancisco BarrancoJavier DiazSilvio P. SabatiniAgostino GibaldiThis paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation with respect to a static camera setup, where the disparity is strictly 1-D after the image rectification. The interaction between vision and motor control allows us to develop an active sensor that achieves high accuracy of the disparity computation around the fixation point, and fast reaction time for the vergence control. In this contribution, we address the development of a real-time architecture for vector disparity computation using an FPGA device. We implement the disparity unit and the control module for vergence, version, and tilt to determine the fixation point. In addition, two on-chip different alternatives for the vector disparity engines are discussed based on the luminance (gradient-based) and phase information of the binocular images. The multiscale versions of these engines are able to estimate the vector disparity up to 32 fps on VGA resolution images with very good accuracy as shown using benchmark sequences with known ground-truth. The performances in terms of frame-rate, resource utilization, and accuracy of the presented approaches are discussed. On the basis of these results, our study indicates that the gradient-based approach leads to the best trade-off choice for the integration with the active vision system.http://www.mdpi.com/1424-8220/12/2/1771/field programmable gate arraysactive visionreal time systems
collection DOAJ
language English
format Article
sources DOAJ
author Eduardo Ros
Francisco Barranco
Javier Diaz
Silvio P. Sabatini
Agostino Gibaldi
spellingShingle Eduardo Ros
Francisco Barranco
Javier Diaz
Silvio P. Sabatini
Agostino Gibaldi
Vector Disparity Sensor with Vergence Control for Active Vision Systems
Sensors
field programmable gate arrays
active vision
real time systems
author_facet Eduardo Ros
Francisco Barranco
Javier Diaz
Silvio P. Sabatini
Agostino Gibaldi
author_sort Eduardo Ros
title Vector Disparity Sensor with Vergence Control for Active Vision Systems
title_short Vector Disparity Sensor with Vergence Control for Active Vision Systems
title_full Vector Disparity Sensor with Vergence Control for Active Vision Systems
title_fullStr Vector Disparity Sensor with Vergence Control for Active Vision Systems
title_full_unstemmed Vector Disparity Sensor with Vergence Control for Active Vision Systems
title_sort vector disparity sensor with vergence control for active vision systems
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2012-02-01
description This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation with respect to a static camera setup, where the disparity is strictly 1-D after the image rectification. The interaction between vision and motor control allows us to develop an active sensor that achieves high accuracy of the disparity computation around the fixation point, and fast reaction time for the vergence control. In this contribution, we address the development of a real-time architecture for vector disparity computation using an FPGA device. We implement the disparity unit and the control module for vergence, version, and tilt to determine the fixation point. In addition, two on-chip different alternatives for the vector disparity engines are discussed based on the luminance (gradient-based) and phase information of the binocular images. The multiscale versions of these engines are able to estimate the vector disparity up to 32 fps on VGA resolution images with very good accuracy as shown using benchmark sequences with known ground-truth. The performances in terms of frame-rate, resource utilization, and accuracy of the presented approaches are discussed. On the basis of these results, our study indicates that the gradient-based approach leads to the best trade-off choice for the integration with the active vision system.
topic field programmable gate arrays
active vision
real time systems
url http://www.mdpi.com/1424-8220/12/2/1771/
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