Results 241 to 250 of about 40,421 (274)

Crowd Density Estimation Using Wireless Sensor Networks

2011 Seventh International Conference on Mobile Ad-hoc and Sensor Networks, 2011
Estimation of crowd distribution is critical to various applications. Although most researches have provided solutions based on images and videos technologies, the high costs for deploying and an over-dependence on the bright light restrict its scope of application.
Yaoxuan Yuan, Chen Qiu, Wei Xi, Jizhong Zhao   +3 more
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Crowd Density Estimation Based on Frequency Analysis

2011 Seventh International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2011
Numerous accidents from crowd stampedes have been recorded in human history, Therefore, the public has set high priority on the safety of public places. Surveillances systems aim to use artificial intelligence to address this problem, so that the crowd accident can be significantly reduced. We adopt a low cost camera to gather visual data and propose a
Wei-Lieh Hsu, Kun-Fong Lin, Chang-Lung Tsai   +2 more
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Multiple features fusion for crowd density estimation

Proceedings of the 4th International Conference on Internet Multimedia Computing and Service, 2012
Crowd density estimation, is much valuable in intelligent crowd monitoring. The traditional approach based on static texture analysis of single frame, is not adept to complex background, and the rule based statistic approaches are short of robustness for background noise.
Zi Ye, Jinqiao Wang, Zhenchong Wang, Hanqing Lu   +3 more
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Estimating crowd density with Minkowski fractal dimension

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999
The estimation of the number of people in an area under surveillance is very important for the problem of crowd monitoring. When an area reaches an occupation level greater than the projected one, people's safety can be in danger. This paper describes a new technique for crowd density estimation based on Minkowski fractal dimension.
A.N. Marana, L. Da Fontoura Costa, R.A. Lotufo, S.A. Velastin   +3 more
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Automatic estimation of crowd density using texture

Safety Science, 1998
This paper considers the role of automatic estimation of crowd density and its importance for the automatic monitoring of areas where crowds are expected to be present. A new technique is proposed which is able to estimate densities ranging from very low to very high concentration of people, which is a difficult problem because in a crowd only parts of
Marana, A. N., Velastin, S. A., Costa, L. F., Lotufo, R. A.   +3 more
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Crowd Density Estimation Using Multi-class Adaboost

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance, 2012
In this paper, we propose a crowd density estimation algorithm based on multi-class Adaboost using spectral texture features. Conventional methods based on self-organizing maps have shown unsatisfactory performance in practical scenarios, and in particular, they have exhibited abrupt degradation in performance under special conditions of crowd ...
Daehum Kim, Younghyun Lee, Bonhwa Ku, Hanseok Ko   +3 more
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Crowd density estimation from a surveillance camera

2020
This chapter presents an approach for crowd density estimation in public scenes from a surveillance camera. We formulate the problem of estimating density in a structured learning framework applied to random decision forests. Our approach learns the mapping between image patch features and relative locations of all the objects inside each patch, which ...
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Crowd Density Estimation Based on Texture Feature Extraction

Journal of Multimedia, 2013
As we know, feature extraction has an important role in crowd density estimation. In our paper, we introduce a new texture feature called Tamura, which is usually used in image retrieval algorithms. On the other hand, the time consuming is another issue that must be considered, especially for the real-time application of the crowd density estimation ...
Bobo Wang, Hong Bao, Shan Yang, Haitao Lou   +3 more
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Scale-Informed Density Estimation for Dense Crowd Counting

2019 IEEE Visual Communications and Image Processing (VCIP), 2019
Dense crowd counting (DCC) remains challenging due to the scale variation and occlusion. Several deep learning based DCC methods have achieved the state-of-arts on public datasets. However, experimental results show that the scale variation is still the main factor to hinder the DCC performance.
Zirui Li, Yuexian Zou, Guoshuai Wang, Jian Zhang   +3 more
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Crowd Density Estimation for Public Transport Vehicles [PDF]

, 2014
OA ...
Handte, Marcus, Iqbal, Muhammad Umer, Wagner, Stephan, Apolinarski, Wolfgang, Marrón, Pedro José, Navarro, Eva Maria Muñoz, Martinez, Santiago, Barthelemy, Sara Izquierdo   +7 more
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