PDE-based disparity estimation with occlusion and texture handling for accurate depth recovery from a stereo image pair
PDE-based disparity estimation with occlusion and texture handling for accurate depth recovery from a stereo image pair
This paper presents a novel PDE-based method for floatingpoint disparity estimation which produces smooth disparity fields with sharp object boundaries for surface reconstruction. In order to avoid the over-segmentation problem of image-driven structure tensor and the blurred boundary problem of field-driven tensor, we propose a new anisotropic diffusivity function controlled by image and disparity gradients. We also embed a bi-directional disparity matching term to control the data term in occluded regions. We evaluate the proposed method on data sets from the Middlebury benchmarking site and real data sets with ground-truth models scanned by a LIDAR sensor. © 2010 IEEE.
Anisotropic diffusivity, Bi-directional, Boundary problems, Data sets, Data terms, Depth recovery, Disparity estimations, Floatingpoint, LIDAR sensors, Occlusion handling, Over segmentation, Real data sets, Sharp objects, Stereo image pairs, Structure tensors, Variational methods, Estimation, Image segmentation, Imaging systems, Optical radar, Ordinary differential equations, Tensors, Surface reconstruction
4061-4064
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
3 December 2010
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
Kim, H. and Hilton, Adrian
(2010)
PDE-based disparity estimation with occlusion and texture handling for accurate depth recovery from a stereo image pair.
17th IEEE International Conference on Image Processing, Hong Kong.
26 - 29 Sep 2010.
.
(doi:10.1109/ICIP.2010.5654067).
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper presents a novel PDE-based method for floatingpoint disparity estimation which produces smooth disparity fields with sharp object boundaries for surface reconstruction. In order to avoid the over-segmentation problem of image-driven structure tensor and the blurred boundary problem of field-driven tensor, we propose a new anisotropic diffusivity function controlled by image and disparity gradients. We also embed a bi-directional disparity matching term to control the data term in occluded regions. We evaluate the proposed method on data sets from the Middlebury benchmarking site and real data sets with ground-truth models scanned by a LIDAR sensor. © 2010 IEEE.
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Published date: 3 December 2010
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cited By 0
Venue - Dates:
17th IEEE International Conference on Image Processing, Hong Kong, 2010-09-26 - 2010-09-29
Keywords:
Anisotropic diffusivity, Bi-directional, Boundary problems, Data sets, Data terms, Depth recovery, Disparity estimations, Floatingpoint, LIDAR sensors, Occlusion handling, Over segmentation, Real data sets, Sharp objects, Stereo image pairs, Structure tensors, Variational methods, Estimation, Image segmentation, Imaging systems, Optical radar, Ordinary differential equations, Tensors, Surface reconstruction
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Local EPrints ID: 440577
URI: http://eprints.soton.ac.uk/id/eprint/440577
PURE UUID: 30821d06-07e0-4cac-b790-cbc5d37414e1
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Date deposited: 07 May 2020 16:37
Last modified: 17 Mar 2024 04:01
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Author:
H. Kim
Author:
Adrian Hilton
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