The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
큰 계산 복잡성으로 인해 실시간 애플리케이션 시나리오에서 스테레오 매칭이 큰 과제가 됩니다. 비디오 시퀀스의 스테레오 매칭 문제는 비디오 프레임 간에 시간적 상관관계가 존재하기 때문에 정지영상의 문제와 약간 다릅니다. 그러나 알고리즘 가속을 위해 시차의 시간적 일관성을 고려한 기존 방법은 없습니다. 본 연구에서는 시차 검색 범위를 좁혀 매칭 비용 계산 및 비용 집계 단계를 최적화하기 위한 동적 시차 범위(Dynamic Disparity Range, DDR)라는 기법과 비용 집계 단계를 최적화하기 위해 임시 비용 집계 경로(Temporal Cost Aggregation Path)라는 기법을 제안했다. 이러한 방식을 기반으로 비디오 시퀀스의 스테레오 매칭을 위한 DDR-SGM 및 DDR-MCCNN 알고리즘을 제안했습니다. 평가 결과, 제안된 알고리즘은 정확도의 손실이 거의 없이 계산 복잡도를 크게 감소시키는 것으로 나타났습니다. 우리는 제안된 스테레오 매칭 최적화가 효과적이며 스테레오 비디오의 시간적 일관성이 정확도를 높이거나 계산 복잡성을 줄이는 데 매우 유용하다는 것을 증명했습니다.
Ming LI
Nanjing University
Li SHI
Nanjing University
Xudong CHEN
Nanjing University
Sidan DU
Nanjing University
Yang LI
Nanjing University
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부
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
부
@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},}
부
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 -