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
배경 모델링은 비디오 시퀀스의 모션 감지에서 가장 어렵고 시간이 많이 걸리는 작업 중 하나입니다. 본 논문에서는 마지막 3개 프레임의 시공간 정보를 활용한 배경 독립 이동체 분할 알고리즘을 제시한다. 기존의 3프레임 기반 방법은 차이 이미지의 중첩 영역에서 미미한 기울기 정보와 가장자리 위치 파악 오류로 인해 문제에 직면해 있습니다. 이러한 방법은 흩어져 있는 움직이는 가장자리를 추출하고 특히 장면에 느리게 움직이는 객체가 있는 경우 감지율이 낮습니다. 게다가 움직이는 물체를 분할하고 추적하는 데에는 적합하지 않습니다. 제안된 방법은 에지를 세그먼트로 표현하고 거리 변환을 통한 기울기 누적을 활용하는 새로운 세그먼트 기반의 유연한 에지 매칭 알고리즘을 적용하여 이러한 문제를 해결합니다. 가장 최근의 프레임 3개를 사용하므로 제안된 방법은 환경 변화에 적응할 수 있습니다. 세그먼트 기반 표현은 로컬 기하학적 변환을 촉진하므로 유연한 매칭을 적절하게 사용하여 효과적인 추적 솔루션을 제공할 수 있습니다. 감지된 움직이는 가장자리에서 움직이는 객체 영역을 분할하기 위해 유역 기반 알고리즘을 도입한 다음 반복적인 배경 제거 절차를 수행합니다. 유역 기반 분할 알고리즘은 보다 정확한 경계로 움직이는 객체를 추출하는 데 도움이 되므로 결국 콘텐츠 기반 응용 프로그램에서 더 높은 코딩 효율성을 달성하고 제한된 비트 전송률 멀티미디어 통신에서도 우수한 시각적 품질을 보장합니다.
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부
M. Ali Akber DEWAN, M. Julius HOSSAIN, Oksam CHAE, "Background Independent Moving Object Segmentation for Video Surveillance" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 2, pp. 585-598, February 2009, doi: 10.1587/transcom.E92.B.585.
Abstract: Background modeling is one of the most challenging and time consuming tasks in motion detection from video sequence. This paper presents a background independent moving object segmentation algorithm utilizing the spatio-temporal information of the last three frames. Existing three-frame based methods face challenges due to the insignificant gradient information in the overlapping region of difference images and edge localization errors. These methods extract scattered moving edges and experience poor detection rate especially when objects with slow movement exist in the scene. Moreover, they are not much suitable for moving object segmentation and tracking. The proposed method solves these problems by representing edges as segments and applying a novel segment based flexible edge matching algorithm which makes use of gradient accumulation through distance transformation. Due to working with three most recent frames, the proposed method can adapt to changes in the environment. Segment based representation facilitates local geometric transformation and thus it can make proper use of flexible matching to provide an effective solution for tracking. To segment the moving object region from the detected moving edges, we introduce a watershed based algorithm followed by an iterative background removal procedure. Watershed based segmentation algorithm helps to extract moving object with more accurate boundary which eventually achieves higher coding efficiency in content based applications and ensures a good visual quality even in the limited bit rate multimedia communication.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.585/_p
부
@ARTICLE{e92-b_2_585,
author={M. Ali Akber DEWAN, M. Julius HOSSAIN, Oksam CHAE, },
journal={IEICE TRANSACTIONS on Communications},
title={Background Independent Moving Object Segmentation for Video Surveillance},
year={2009},
volume={E92-B},
number={2},
pages={585-598},
abstract={Background modeling is one of the most challenging and time consuming tasks in motion detection from video sequence. This paper presents a background independent moving object segmentation algorithm utilizing the spatio-temporal information of the last three frames. Existing three-frame based methods face challenges due to the insignificant gradient information in the overlapping region of difference images and edge localization errors. These methods extract scattered moving edges and experience poor detection rate especially when objects with slow movement exist in the scene. Moreover, they are not much suitable for moving object segmentation and tracking. The proposed method solves these problems by representing edges as segments and applying a novel segment based flexible edge matching algorithm which makes use of gradient accumulation through distance transformation. Due to working with three most recent frames, the proposed method can adapt to changes in the environment. Segment based representation facilitates local geometric transformation and thus it can make proper use of flexible matching to provide an effective solution for tracking. To segment the moving object region from the detected moving edges, we introduce a watershed based algorithm followed by an iterative background removal procedure. Watershed based segmentation algorithm helps to extract moving object with more accurate boundary which eventually achieves higher coding efficiency in content based applications and ensures a good visual quality even in the limited bit rate multimedia communication.},
keywords={},
doi={10.1587/transcom.E92.B.585},
ISSN={1745-1345},
month={February},}
부
TY - JOUR
TI - Background Independent Moving Object Segmentation for Video Surveillance
T2 - IEICE TRANSACTIONS on Communications
SP - 585
EP - 598
AU - M. Ali Akber DEWAN
AU - M. Julius HOSSAIN
AU - Oksam CHAE
PY - 2009
DO - 10.1587/transcom.E92.B.585
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2009
AB - Background modeling is one of the most challenging and time consuming tasks in motion detection from video sequence. This paper presents a background independent moving object segmentation algorithm utilizing the spatio-temporal information of the last three frames. Existing three-frame based methods face challenges due to the insignificant gradient information in the overlapping region of difference images and edge localization errors. These methods extract scattered moving edges and experience poor detection rate especially when objects with slow movement exist in the scene. Moreover, they are not much suitable for moving object segmentation and tracking. The proposed method solves these problems by representing edges as segments and applying a novel segment based flexible edge matching algorithm which makes use of gradient accumulation through distance transformation. Due to working with three most recent frames, the proposed method can adapt to changes in the environment. Segment based representation facilitates local geometric transformation and thus it can make proper use of flexible matching to provide an effective solution for tracking. To segment the moving object region from the detected moving edges, we introduce a watershed based algorithm followed by an iterative background removal procedure. Watershed based segmentation algorithm helps to extract moving object with more accurate boundary which eventually achieves higher coding efficiency in content based applications and ensures a good visual quality even in the limited bit rate multimedia communication.
ER -