Computing 2-D Motion Field with Multi-Resolution Images and Cooperation of Gradient-Based and Matching-Based Schemes
Summary :
A new approach is presented for the detection and computation of a two-dimensional motion field in image sequences. This computational model has a multi-channel motion detector and an optimal motion selector. In the motion detector, each channel has an inherent spatial resolution. The detector computes a two-dimensional motion field by the gradient-based method in parallel. The motion selector compares those candidates of the motion field by a correlation value of the intensity patterns hierarchically arranged from low to high resolution. It then determines the most probable motion for each image point. Experimental results are shown for synthetic images. This model can detect more reliable motion fields than the conventional one-chanel model.
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- IEICE TRANSACTIONS on Fundamentals Vol.E78-A No.6 pp.685-692
- Publication Date
- 1995/06/25
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- Special Section PAPER (Special Section of Papers Selected from 1994 Joint Technical Conference on Circuits/Systems, Computers and Communications (JTC-CSCC '94))
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Norio TAGAWA, Tadashi MORIYA, "Computing 2-D Motion Field with Multi-Resolution Images and Cooperation of Gradient-Based and Matching-Based Schemes" in IEICE TRANSACTIONS on Fundamentals,
vol. E78-A, no. 6, pp. 685-692, June 1995, doi: .
Abstract: A new approach is presented for the detection and computation of a two-dimensional motion field in image sequences. This computational model has a multi-channel motion detector and an optimal motion selector. In the motion detector, each channel has an inherent spatial resolution. The detector computes a two-dimensional motion field by the gradient-based method in parallel. The motion selector compares those candidates of the motion field by a correlation value of the intensity patterns hierarchically arranged from low to high resolution. It then determines the most probable motion for each image point. Experimental results are shown for synthetic images. This model can detect more reliable motion fields than the conventional one-chanel model.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e78-a_6_685/_p
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@ARTICLE{e78-a_6_685,
author={Norio TAGAWA, Tadashi MORIYA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Computing 2-D Motion Field with Multi-Resolution Images and Cooperation of Gradient-Based and Matching-Based Schemes},
year={1995},
volume={E78-A},
number={6},
pages={685-692},
abstract={A new approach is presented for the detection and computation of a two-dimensional motion field in image sequences. This computational model has a multi-channel motion detector and an optimal motion selector. In the motion detector, each channel has an inherent spatial resolution. The detector computes a two-dimensional motion field by the gradient-based method in parallel. The motion selector compares those candidates of the motion field by a correlation value of the intensity patterns hierarchically arranged from low to high resolution. It then determines the most probable motion for each image point. Experimental results are shown for synthetic images. This model can detect more reliable motion fields than the conventional one-chanel model.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Computing 2-D Motion Field with Multi-Resolution Images and Cooperation of Gradient-Based and Matching-Based Schemes
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 685
EP - 692
AU - Norio TAGAWA
AU - Tadashi MORIYA
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E78-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1995
AB - A new approach is presented for the detection and computation of a two-dimensional motion field in image sequences. This computational model has a multi-channel motion detector and an optimal motion selector. In the motion detector, each channel has an inherent spatial resolution. The detector computes a two-dimensional motion field by the gradient-based method in parallel. The motion selector compares those candidates of the motion field by a correlation value of the intensity patterns hierarchically arranged from low to high resolution. It then determines the most probable motion for each image point. Experimental results are shown for synthetic images. This model can detect more reliable motion fields than the conventional one-chanel model.
ER -
English
