Estimating Number of People Using Calibrated Monocular Camera Based on Geometrical Analysis of Surface Area
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E92-A No.8 pp.1932-1938
- Publication Date
- 2009/08/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E92.A.1932
- Type of Manuscript
- Special Section PAPER (Special Section on Signal Processing)
- Category
- Image
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
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
Copy
@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},}
Copy
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 -
English
