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
우리는 인접한 지역 수준 특징의 쌍별 상호 작용을 계산하여 객체 모양의 상위 수준 속성을 캡처하는 FIND(Feature Interaction Descriptor)라는 새로운 표현을 제안합니다. 보행자 감지 작업을 처리하기 위해 지역 수준의 특징으로 지역화된 기울기 히스토그램을 사용하고 적절한 히스토그램 유사성 함수를 사용하여 인접한 히스토그램 요소 간의 상호 작용을 측정합니다. 실험 결과는 우리의 설명자가 HOG를 크게 향상시키고 GLAC 및 CoHOG와 같은 관련 고급 기능보다 성능이 우수하다는 것을 보여줍니다.
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부
Hui CAO, Koichiro YAMAGUCHI, Mitsuhiko OHTA, Takashi NAITO, Yoshiki NINOMIYA, "Feature Interaction Descriptor for Pedestrian Detection" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 9, pp. 2656-2659, September 2010, doi: 10.1587/transinf.E93.D.2656.
Abstract: We propose a novel representation called Feature Interaction Descriptor (FIND) to capture high-level properties of object appearance by computing pairwise interactions of adjacent region-level features. In order to deal with pedestrian detection task, we employ localized oriented gradient histograms as region-level features and measure interactions between adjacent histogram elements with a suitable histogram-similarity function. The experimental results show that our descriptor improves upon HOG significantly and outperforms related high-level features such as GLAC and CoHOG.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.2656/_p
부
@ARTICLE{e93-d_9_2656,
author={Hui CAO, Koichiro YAMAGUCHI, Mitsuhiko OHTA, Takashi NAITO, Yoshiki NINOMIYA, },
journal={IEICE TRANSACTIONS on Information},
title={Feature Interaction Descriptor for Pedestrian Detection},
year={2010},
volume={E93-D},
number={9},
pages={2656-2659},
abstract={We propose a novel representation called Feature Interaction Descriptor (FIND) to capture high-level properties of object appearance by computing pairwise interactions of adjacent region-level features. In order to deal with pedestrian detection task, we employ localized oriented gradient histograms as region-level features and measure interactions between adjacent histogram elements with a suitable histogram-similarity function. The experimental results show that our descriptor improves upon HOG significantly and outperforms related high-level features such as GLAC and CoHOG.},
keywords={},
doi={10.1587/transinf.E93.D.2656},
ISSN={1745-1361},
month={September},}
부
TY - JOUR
TI - Feature Interaction Descriptor for Pedestrian Detection
T2 - IEICE TRANSACTIONS on Information
SP - 2656
EP - 2659
AU - Hui CAO
AU - Koichiro YAMAGUCHI
AU - Mitsuhiko OHTA
AU - Takashi NAITO
AU - Yoshiki NINOMIYA
PY - 2010
DO - 10.1587/transinf.E93.D.2656
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2010
AB - We propose a novel representation called Feature Interaction Descriptor (FIND) to capture high-level properties of object appearance by computing pairwise interactions of adjacent region-level features. In order to deal with pedestrian detection task, we employ localized oriented gradient histograms as region-level features and measure interactions between adjacent histogram elements with a suitable histogram-similarity function. The experimental results show that our descriptor improves upon HOG significantly and outperforms related high-level features such as GLAC and CoHOG.
ER -