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
본 논문에서는 스테레오 비전에서 조밀한 시차 지도를 추정하기 위한 새로운 로컬 매칭 알고리즘을 제시하며, 두 단계로 구성된다. 첫 번째 단계에서는 검색 공간의 축소가 높은 효율성으로 수행됩니다. 즉, 픽셀당 평균 후보자 수의 현저한 감소, 낮은 계산 비용 및 정답 유지에 대한 높은 확신을 가지고 수행됩니다. 여러 방사형 창, 강도 정보 및 일부 일반적이고 새로운 제약 조건을 합리적인 방식으로 효과적으로 사용하기 때문에 발생하는 이 결과는 더 많은 제약 조건을 충족하고 특히 지원 창 사용 시 암시된 가정을 충족하는 데 더 유망한 후보를 유지합니다. 즉, 창 픽셀의 불일치 일관성입니다. 이러한 1단계 출력은 검색 공간 감소로 인해 11단계에서 최종 시차 선택 속도가 빨라지는 동시에, 신뢰성 있는 후보자가 많아 더욱 정확한 결과를 약속할 수 있다. 두 번째 단계에서는 가중치가 적용된 창이 반드시 배타적인 선택은 아니지만 사용 및 검사됩니다. 개발된 알고리즘에 대한 표준 스테레오 벤치마크에 대한 실험 결과가 제시되어 있으며, 가중치 창에서 보다 정확한 매칭 비용을 얻기 위한 대규모 계산이 약 XNUMX/XNUMX로 감소하고 최종 시차 맵도 개선되었음을 확인했습니다.
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부
Ali M. FOTOUHI, Abolghasem A. RAIE, "An Efficient Local Stereo Matching Algorithm for Dense Disparity Map Estimation Based on More Effective Use of Intensity Information and Matching Constraints" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 5, pp. 1159-1167, May 2009, doi: 10.1587/transinf.E92.D.1159.
Abstract: In this paper, a new local matching algorithm, to estimate dense disparity map in stereo vision, consisting of two stages is presented. At the first stage, the reduction of search space is carried out with a high efficiency, i.e. remarkable decrease in the average number of candidates per pixel, with low computational cost and high assurance of retaining the correct answer. This outcome being due to the effective use of multiple radial windows, intensity information, and some usual and new constraints, in a reasonable manner, retains those candidates which satisfy more constraints and especially being more promising to satisfy the implied assumption in using support windows; i.e., the disparity consistency of the window pixels. Such an output from the first stage, while speeding up the final selection of disparity in the second stage due to search space reduction, is also promising a more accurate result due to having more reliable candidates. In the second stage, the weighted window, although not necessarily being the exclusive choice, is employed and examined. The experimental results on the standard stereo benchmarks for the developed algorithm are presented, confirming that the massive computations to obtain more precise matching costs in weighted window is reduced to about 1/11 and the final disparity map is also improved.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.1159/_p
부
@ARTICLE{e92-d_5_1159,
author={Ali M. FOTOUHI, Abolghasem A. RAIE, },
journal={IEICE TRANSACTIONS on Information},
title={An Efficient Local Stereo Matching Algorithm for Dense Disparity Map Estimation Based on More Effective Use of Intensity Information and Matching Constraints},
year={2009},
volume={E92-D},
number={5},
pages={1159-1167},
abstract={In this paper, a new local matching algorithm, to estimate dense disparity map in stereo vision, consisting of two stages is presented. At the first stage, the reduction of search space is carried out with a high efficiency, i.e. remarkable decrease in the average number of candidates per pixel, with low computational cost and high assurance of retaining the correct answer. This outcome being due to the effective use of multiple radial windows, intensity information, and some usual and new constraints, in a reasonable manner, retains those candidates which satisfy more constraints and especially being more promising to satisfy the implied assumption in using support windows; i.e., the disparity consistency of the window pixels. Such an output from the first stage, while speeding up the final selection of disparity in the second stage due to search space reduction, is also promising a more accurate result due to having more reliable candidates. In the second stage, the weighted window, although not necessarily being the exclusive choice, is employed and examined. The experimental results on the standard stereo benchmarks for the developed algorithm are presented, confirming that the massive computations to obtain more precise matching costs in weighted window is reduced to about 1/11 and the final disparity map is also improved.},
keywords={},
doi={10.1587/transinf.E92.D.1159},
ISSN={1745-1361},
month={May},}
부
TY - JOUR
TI - An Efficient Local Stereo Matching Algorithm for Dense Disparity Map Estimation Based on More Effective Use of Intensity Information and Matching Constraints
T2 - IEICE TRANSACTIONS on Information
SP - 1159
EP - 1167
AU - Ali M. FOTOUHI
AU - Abolghasem A. RAIE
PY - 2009
DO - 10.1587/transinf.E92.D.1159
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2009
AB - In this paper, a new local matching algorithm, to estimate dense disparity map in stereo vision, consisting of two stages is presented. At the first stage, the reduction of search space is carried out with a high efficiency, i.e. remarkable decrease in the average number of candidates per pixel, with low computational cost and high assurance of retaining the correct answer. This outcome being due to the effective use of multiple radial windows, intensity information, and some usual and new constraints, in a reasonable manner, retains those candidates which satisfy more constraints and especially being more promising to satisfy the implied assumption in using support windows; i.e., the disparity consistency of the window pixels. Such an output from the first stage, while speeding up the final selection of disparity in the second stage due to search space reduction, is also promising a more accurate result due to having more reliable candidates. In the second stage, the weighted window, although not necessarily being the exclusive choice, is employed and examined. The experimental results on the standard stereo benchmarks for the developed algorithm are presented, confirming that the massive computations to obtain more precise matching costs in weighted window is reduced to about 1/11 and the final disparity map is also improved.
ER -