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".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Nous proposons une nouvelle technique pour estimer le nombre de personnes dans une séquence vidéo ; il présente l’avantage d’être stable même dans des situations de surpeuplement et de ne nécessiter aucune donnée de vérité sur le terrain. En analysant quantitativement les relations géométriques entre les pixels de l’image et leurs volumes d’intersection dans le monde réel, une image de premier plan indique directement le nombre de personnes. Etant donné que la détection au premier plan est possible même dans des situations de foule, la méthode proposée peut être appliquée dans de telles situations. De plus, il peut estimer le nombre de personnes de manière a priori, de sorte qu’il n’a pas besoin de données de vérité sur le terrain, contrairement aux techniques d’estimation existantes basées sur les caractéristiques. Les expériences montrent la validité de la méthode proposée.
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Hiroyuki ARAI, Isao MIYAGAWA, Hideki KOIKE, Miki HASEYAMA, "Estimating Number of People Using Calibrated Monocular Camera Based on Geometrical Analysis of Surface Area" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 8, pp. 1932-1938, August 2009, doi: 10.1587/transfun.E92.A.1932.
Abstract: We propose a novel technique for estimating the number of people in a video sequence; it has the advantages of being stable even in crowded situations and needing no ground-truth data. By analyzing the geometrical relationships between image pixels and their intersection volumes in the real world quantitatively, a foreground image directly indicates the number of people. Because foreground detection is possible even in crowded situations, the proposed method can be applied in such situations. Moreover, it can estimate the number of people in an a priori manner, so it needs no ground-truth data unlike existing feature-based estimation techniques. Experiments show the validity of the proposed method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.1932/_p
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@ARTICLE{e92-a_8_1932,
author={Hiroyuki ARAI, Isao MIYAGAWA, Hideki KOIKE, Miki HASEYAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Estimating Number of People Using Calibrated Monocular Camera Based on Geometrical Analysis of Surface Area},
year={2009},
volume={E92-A},
number={8},
pages={1932-1938},
abstract={We propose a novel technique for estimating the number of people in a video sequence; it has the advantages of being stable even in crowded situations and needing no ground-truth data. By analyzing the geometrical relationships between image pixels and their intersection volumes in the real world quantitatively, a foreground image directly indicates the number of people. Because foreground detection is possible even in crowded situations, the proposed method can be applied in such situations. Moreover, it can estimate the number of people in an a priori manner, so it needs no ground-truth data unlike existing feature-based estimation techniques. Experiments show the validity of the proposed method.},
keywords={},
doi={10.1587/transfun.E92.A.1932},
ISSN={1745-1337},
month={August},}
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TY - JOUR
TI - Estimating Number of People Using Calibrated Monocular Camera Based on Geometrical Analysis of Surface Area
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1932
EP - 1938
AU - Hiroyuki ARAI
AU - Isao MIYAGAWA
AU - Hideki KOIKE
AU - Miki HASEYAMA
PY - 2009
DO - 10.1587/transfun.E92.A.1932
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2009
AB - We propose a novel technique for estimating the number of people in a video sequence; it has the advantages of being stable even in crowded situations and needing no ground-truth data. By analyzing the geometrical relationships between image pixels and their intersection volumes in the real world quantitatively, a foreground image directly indicates the number of people. Because foreground detection is possible even in crowded situations, the proposed method can be applied in such situations. Moreover, it can estimate the number of people in an a priori manner, so it needs no ground-truth data unlike existing feature-based estimation techniques. Experiments show the validity of the proposed method.
ER -