IEICE TRANSACTIONS on Information
Using Temporal Correlation to Optimize Stereo Matching in Video Sequences
Summary :
The large computational complexity makes stereo matching a big challenge in real-time application scenario. The problem of stereo matching in a video sequence is slightly different with that in a still image because there exists temporal correlation among video frames. However, no existing method considered temporal consistency of disparity for algorithm acceleration. In this work, we proposed a scheme called the dynamic disparity range (DDR) to optimize matching cost calculation and cost aggregation steps by narrowing disparity searching range, and a scheme called temporal cost aggregation path to optimize the cost aggregation step. Based on the schemes, we proposed the DDR-SGM and the DDR-MCCNN algorithms for the stereo matching in video sequences. Evaluation results showed that the proposed algorithms significantly reduced the computational complexity with only very slight loss of accuracy. We proved that the proposed optimizations for the stereo matching are effective and the temporal consistency in stereo video is highly useful for either improving accuracy or reducing computational complexity.
- Publication
- IEICE TRANSACTIONS on Information Vol.E102-D No.6 pp.1183-1196
- Publication Date
- 2019/06/01
- Publicized
- 2019/03/01
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2018EDP7273
- Type of Manuscript
- PAPER
- Category
- Image Recognition, Computer Vision
Authors
Ming LI
Nanjing University
Li SHI
Nanjing University
Xudong CHEN
Nanjing University
Sidan DU
Nanjing University
Yang LI
Nanjing University
Keyword
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Ming LI, Li SHI, Xudong CHEN, Sidan DU, Yang LI, "Using Temporal Correlation to Optimize Stereo Matching in Video Sequences" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 6, pp. 1183-1196, June 2019, doi: 10.1587/transinf.2018EDP7273.
Abstract: The large computational complexity makes stereo matching a big challenge in real-time application scenario. The problem of stereo matching in a video sequence is slightly different with that in a still image because there exists temporal correlation among video frames. However, no existing method considered temporal consistency of disparity for algorithm acceleration. In this work, we proposed a scheme called the dynamic disparity range (DDR) to optimize matching cost calculation and cost aggregation steps by narrowing disparity searching range, and a scheme called temporal cost aggregation path to optimize the cost aggregation step. Based on the schemes, we proposed the DDR-SGM and the DDR-MCCNN algorithms for the stereo matching in video sequences. Evaluation results showed that the proposed algorithms significantly reduced the computational complexity with only very slight loss of accuracy. We proved that the proposed optimizations for the stereo matching are effective and the temporal consistency in stereo video is highly useful for either improving accuracy or reducing computational complexity.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDP7273/_p
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@ARTICLE{e102-d_6_1183,
author={Ming LI, Li SHI, Xudong CHEN, Sidan DU, Yang LI, },
journal={IEICE TRANSACTIONS on Information},
title={Using Temporal Correlation to Optimize Stereo Matching in Video Sequences},
year={2019},
volume={E102-D},
number={6},
pages={1183-1196},
abstract={The large computational complexity makes stereo matching a big challenge in real-time application scenario. The problem of stereo matching in a video sequence is slightly different with that in a still image because there exists temporal correlation among video frames. However, no existing method considered temporal consistency of disparity for algorithm acceleration. In this work, we proposed a scheme called the dynamic disparity range (DDR) to optimize matching cost calculation and cost aggregation steps by narrowing disparity searching range, and a scheme called temporal cost aggregation path to optimize the cost aggregation step. Based on the schemes, we proposed the DDR-SGM and the DDR-MCCNN algorithms for the stereo matching in video sequences. Evaluation results showed that the proposed algorithms significantly reduced the computational complexity with only very slight loss of accuracy. We proved that the proposed optimizations for the stereo matching are effective and the temporal consistency in stereo video is highly useful for either improving accuracy or reducing computational complexity.},
keywords={},
doi={10.1587/transinf.2018EDP7273},
ISSN={1745-1361},
month={June},}
Copy
TY - JOUR
TI - Using Temporal Correlation to Optimize Stereo Matching in Video Sequences
T2 - IEICE TRANSACTIONS on Information
SP - 1183
EP - 1196
AU - Ming LI
AU - Li SHI
AU - Xudong CHEN
AU - Sidan DU
AU - Yang LI
PY - 2019
DO - 10.1587/transinf.2018EDP7273
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2019
AB - The large computational complexity makes stereo matching a big challenge in real-time application scenario. The problem of stereo matching in a video sequence is slightly different with that in a still image because there exists temporal correlation among video frames. However, no existing method considered temporal consistency of disparity for algorithm acceleration. In this work, we proposed a scheme called the dynamic disparity range (DDR) to optimize matching cost calculation and cost aggregation steps by narrowing disparity searching range, and a scheme called temporal cost aggregation path to optimize the cost aggregation step. Based on the schemes, we proposed the DDR-SGM and the DDR-MCCNN algorithms for the stereo matching in video sequences. Evaluation results showed that the proposed algorithms significantly reduced the computational complexity with only very slight loss of accuracy. We proved that the proposed optimizations for the stereo matching are effective and the temporal consistency in stereo video is highly useful for either improving accuracy or reducing computational complexity.
ER -
English
