Parametric Estimation of Optical Flow from Two Perspective Views
Summary :
Since the detection of optical flow (two-dimensional motion field on an image) from image sequences is essentially an ill-posed problem, most of the conventional methods use a smoothness constraint for optical flow heuristically and detect reasonable optical flow. However, little discussion exists regarding the degree of smoothness. Furthermore, to recover the relative three-dimensional motion and depth between a camera and a rigid object, in general at first, the optical flow is detected without a rigid motion constraint, and next, the motion and depth are estimated using the detected optical flow. Rigorously speaking, the optical flow should be detected with such a constraint, and consequently three-dimensional motion and depth should be determined. To solve these problems, in this paper, we apply a parametric model to an optical flow, and construct an estimation algorithm based on this model.
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- IEICE TRANSACTIONS on Information Vol.E84-D No.4 pp.485-494
- Publication Date
- 2001/04/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Image Processing, Image Pattern Recognition
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Norio TAGAWA, Atsuya INAGAKI, Akihiro MINAGAWA, "Parametric Estimation of Optical Flow from Two Perspective Views" in IEICE TRANSACTIONS on Information,
vol. E84-D, no. 4, pp. 485-494, April 2001, doi: .
Abstract: Since the detection of optical flow (two-dimensional motion field on an image) from image sequences is essentially an ill-posed problem, most of the conventional methods use a smoothness constraint for optical flow heuristically and detect reasonable optical flow. However, little discussion exists regarding the degree of smoothness. Furthermore, to recover the relative three-dimensional motion and depth between a camera and a rigid object, in general at first, the optical flow is detected without a rigid motion constraint, and next, the motion and depth are estimated using the detected optical flow. Rigorously speaking, the optical flow should be detected with such a constraint, and consequently three-dimensional motion and depth should be determined. To solve these problems, in this paper, we apply a parametric model to an optical flow, and construct an estimation algorithm based on this model.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_4_485/_p
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@ARTICLE{e84-d_4_485,
author={Norio TAGAWA, Atsuya INAGAKI, Akihiro MINAGAWA, },
journal={IEICE TRANSACTIONS on Information},
title={Parametric Estimation of Optical Flow from Two Perspective Views},
year={2001},
volume={E84-D},
number={4},
pages={485-494},
abstract={Since the detection of optical flow (two-dimensional motion field on an image) from image sequences is essentially an ill-posed problem, most of the conventional methods use a smoothness constraint for optical flow heuristically and detect reasonable optical flow. However, little discussion exists regarding the degree of smoothness. Furthermore, to recover the relative three-dimensional motion and depth between a camera and a rigid object, in general at first, the optical flow is detected without a rigid motion constraint, and next, the motion and depth are estimated using the detected optical flow. Rigorously speaking, the optical flow should be detected with such a constraint, and consequently three-dimensional motion and depth should be determined. To solve these problems, in this paper, we apply a parametric model to an optical flow, and construct an estimation algorithm based on this model.},
keywords={},
doi={},
ISSN={},
month={April},}
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TY - JOUR
TI - Parametric Estimation of Optical Flow from Two Perspective Views
T2 - IEICE TRANSACTIONS on Information
SP - 485
EP - 494
AU - Norio TAGAWA
AU - Atsuya INAGAKI
AU - Akihiro MINAGAWA
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2001
AB - Since the detection of optical flow (two-dimensional motion field on an image) from image sequences is essentially an ill-posed problem, most of the conventional methods use a smoothness constraint for optical flow heuristically and detect reasonable optical flow. However, little discussion exists regarding the degree of smoothness. Furthermore, to recover the relative three-dimensional motion and depth between a camera and a rigid object, in general at first, the optical flow is detected without a rigid motion constraint, and next, the motion and depth are estimated using the detected optical flow. Rigorously speaking, the optical flow should be detected with such a constraint, and consequently three-dimensional motion and depth should be determined. To solve these problems, in this paper, we apply a parametric model to an optical flow, and construct an estimation algorithm based on this model.
ER -
English
