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Sensors 2012, 12(2), 1771-1799;

Vector Disparity Sensor with Vergence Control for Active Vision Systems

Department of Computer Architecture and Technology, CITIC, ETSIIT, University of Granada, C/Daniel Saucedo Aranda s/n, E18071, Granada, Spain
PSPC Group, Department of Biophysical and Electronic Engineering (DIBE), University of Genoa, Via Opera Pia 11A, I-16145, Genoa, Italy
Author to whom correspondence should be addressed.
Received: 28 December 2011 / Revised: 18 January 2012 / Accepted: 7 February 2012 / Published: 9 February 2012
(This article belongs to the Section Physical Sensors)
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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. View Full-Text
Keywords: field programmable gate arrays; active vision; real time systems field programmable gate arrays; active vision; real time systems

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Barranco, F.; Diaz, J.; Gibaldi, A.; Sabatini, S.P.; Ros, E. Vector Disparity Sensor with Vergence Control for Active Vision Systems. Sensors 2012, 12, 1771-1799.

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