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 항구, 강, 공장 부지 등 광역 감시를 위한 "주파수 패턴 강조 차감(FPES)"이라는 강력한 소형 물체 감지 방법을 제시합니다. 조도, 날씨, 카메라 진동 등 환경 조건의 변화에 따라 강력한 감지를 달성하기 위해 우리의 방법은 대상 물체와 배경 및 소음 사이의 주파수 성분의 차이를 기반으로 대상 물체를 구별합니다. 평가 결과, 우리의 방법은 중앙 95~30m 범위의 대규모 감시 영역 영상에서 대상 물체를 75% 이상 검출한 것으로 나타났다.
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Daisuke ABE, Eigo SEGAWA, Osafumi NAKAYAMA, Morito SHIOHARA, Shigeru SASAKI, Nobuyuki SUGANO, Hajime KANNO, "Robust Small-Object Detection for Outdoor Wide-Area Surveillance" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 7, pp. 1922-1928, July 2008, doi: 10.1093/ietisy/e91-d.7.1922.
Abstract: In this paper, we present a robust small-object detection method, which we call "Frequency Pattern Emphasis Subtraction (FPES)", for wide-area surveillance such as that of harbors, rivers, and plant premises. For achieving robust detection under changes in environmental conditions, such as illuminance level, weather, and camera vibration, our method distinguishes target objects from background and noise based on the differences in frequency components between them. The evaluation results demonstrate that our method detected more than 95% of target objects in the images of large surveillance areas ranging from 30-75 meters at their center.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.7.1922/_p
부
@ARTICLE{e91-d_7_1922,
author={Daisuke ABE, Eigo SEGAWA, Osafumi NAKAYAMA, Morito SHIOHARA, Shigeru SASAKI, Nobuyuki SUGANO, Hajime KANNO, },
journal={IEICE TRANSACTIONS on Information},
title={Robust Small-Object Detection for Outdoor Wide-Area Surveillance},
year={2008},
volume={E91-D},
number={7},
pages={1922-1928},
abstract={In this paper, we present a robust small-object detection method, which we call "Frequency Pattern Emphasis Subtraction (FPES)", for wide-area surveillance such as that of harbors, rivers, and plant premises. For achieving robust detection under changes in environmental conditions, such as illuminance level, weather, and camera vibration, our method distinguishes target objects from background and noise based on the differences in frequency components between them. The evaluation results demonstrate that our method detected more than 95% of target objects in the images of large surveillance areas ranging from 30-75 meters at their center.},
keywords={},
doi={10.1093/ietisy/e91-d.7.1922},
ISSN={1745-1361},
month={July},}
부
TY - JOUR
TI - Robust Small-Object Detection for Outdoor Wide-Area Surveillance
T2 - IEICE TRANSACTIONS on Information
SP - 1922
EP - 1928
AU - Daisuke ABE
AU - Eigo SEGAWA
AU - Osafumi NAKAYAMA
AU - Morito SHIOHARA
AU - Shigeru SASAKI
AU - Nobuyuki SUGANO
AU - Hajime KANNO
PY - 2008
DO - 10.1093/ietisy/e91-d.7.1922
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2008
AB - In this paper, we present a robust small-object detection method, which we call "Frequency Pattern Emphasis Subtraction (FPES)", for wide-area surveillance such as that of harbors, rivers, and plant premises. For achieving robust detection under changes in environmental conditions, such as illuminance level, weather, and camera vibration, our method distinguishes target objects from background and noise based on the differences in frequency components between them. The evaluation results demonstrate that our method detected more than 95% of target objects in the images of large surveillance areas ranging from 30-75 meters at their center.
ER -