Disparity Selection in Binocular Pursuit

Atsuko MAKI; Tomas UHLIN

Disparity Selection in Binocular Pursuit

Atsuko MAKI, Tomas UHLIN

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This paper presents a technique for disparity selection in the context of binocular pursuit. For vergence control in binocular pursuit, it is a crucial problem to find the disparity which corresponds to the target among multiple disparities generally observed in a scene. To solve the problem of the selection, we propose an approach based on histogramming the disparities obtained in the scene. Here we use an extended phase-based disparity estimation algorithm. The idea is to slice the scene using the disparity histogram so that only the target remains. The slice is chosen around a peak in the histogram using prediction of the target disparity and target location obtained by back projection. The tracking of the peak enables robustness against other, possibly dominant, objects in the scene. The approach is investigated through experiments and shown to work appropriately.

Publication: IEICE TRANSACTIONS on Information Vol.E78-D No.12 pp.1591-1597

Publication Date: 1995/12/25

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Type of Manuscript: Special Section PAPER (Special Issue on Machine Vision Applications)

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Atsuko MAKI, Tomas UHLIN, "Disparity Selection in Binocular Pursuit" in IEICE TRANSACTIONS on Information, vol. E78-D, no. 12, pp. 1591-1597, December 1995, doi: .
Abstract: This paper presents a technique for disparity selection in the context of binocular pursuit. For vergence control in binocular pursuit, it is a crucial problem to find the disparity which corresponds to the target among multiple disparities generally observed in a scene. To solve the problem of the selection, we propose an approach based on histogramming the disparities obtained in the scene. Here we use an extended phase-based disparity estimation algorithm. The idea is to slice the scene using the disparity histogram so that only the target remains. The slice is chosen around a peak in the histogram using prediction of the target disparity and target location obtained by back projection. The tracking of the peak enables robustness against other, possibly dominant, objects in the scene. The approach is investigated through experiments and shown to work appropriately.
URL: https://global.ieice.org/en_transactions/information/10.1587/e78-d_12_1591/_p

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@ARTICLE{e78-d_12_1591,
author={Atsuko MAKI, Tomas UHLIN, },
journal={IEICE TRANSACTIONS on Information},
title={Disparity Selection in Binocular Pursuit},
year={1995},
volume={E78-D},
number={12},
pages={1591-1597},
abstract={This paper presents a technique for disparity selection in the context of binocular pursuit. For vergence control in binocular pursuit, it is a crucial problem to find the disparity which corresponds to the target among multiple disparities generally observed in a scene. To solve the problem of the selection, we propose an approach based on histogramming the disparities obtained in the scene. Here we use an extended phase-based disparity estimation algorithm. The idea is to slice the scene using the disparity histogram so that only the target remains. The slice is chosen around a peak in the histogram using prediction of the target disparity and target location obtained by back projection. The tracking of the peak enables robustness against other, possibly dominant, objects in the scene. The approach is investigated through experiments and shown to work appropriately.},
keywords={},
doi={},
ISSN={},
month={December},}

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TY - JOUR
TI - Disparity Selection in Binocular Pursuit
T2 - IEICE TRANSACTIONS on Information
SP - 1591
EP - 1597
AU - Atsuko MAKI
AU - Tomas UHLIN
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E78-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 1995
AB - This paper presents a technique for disparity selection in the context of binocular pursuit. For vergence control in binocular pursuit, it is a crucial problem to find the disparity which corresponds to the target among multiple disparities generally observed in a scene. To solve the problem of the selection, we propose an approach based on histogramming the disparities obtained in the scene. Here we use an extended phase-based disparity estimation algorithm. The idea is to slice the scene using the disparity histogram so that only the target remains. The slice is chosen around a peak in the histogram using prediction of the target disparity and target location obtained by back projection. The tracking of the peak enables robustness against other, possibly dominant, objects in the scene. The approach is investigated through experiments and shown to work appropriately.
ER -