Results 241 to 250 of about 4,036,534 (282)

Vanishing region loss for crowd density estimation

Pattern Recognition Letters, 2020
Abstract Crowd density estimation is a crucial component in surveillance systems to construct safe and efficient urban environments. Due to perspective distortion, individuals in crowd scenes diminish in size as they converge toward the vanishing point. Hence, there are significant visual variations in individuals’ size and appearance, which may lead
Bedir Yilmaz, Siti Norul Huda Sheikh Abdullah, Ven Jyn Kok   +2 more
openaire   +2 more sources

Crowd Density Estimation for Outdoor Environments

Proceedings of the 8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS), 2015
Crowd density analysis is crucial in management and control of the crowds and ensure safety. In this paper, we proposed two crowd density estimation methods using texture descriptors of the image in outdoor scenes. Two methods based on different techniques, one using Local Binary Pattern and Gabor filters, and the other using 5 statistics of Grey Level
Marjan Jalali Moghaddam, Elham Shaabani, Reza Safabakhsh   +2 more
openaire   +1 more source

The application of the binocular camera to crowd density estimation

2012 International Conference on Machine Learning and Cybernetics, 2012
In this paper, a new method is proposed to estimate crowd density based on binocular vision: according to the average parallax of the object in the two camera plane, first we calculate the correction parameters of monitoring location, then we fit the correction function based on the result of the correction parameters of the same target objects in ...
Sen Guo, San-Feng Chen
openaire   +1 more source

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
openaire   +2 more sources

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.
Aparecido Nilceu Marana, Luciano da Fontoura Costa, Roberto de Alencar Lotufo, Sergio A. Velastin   +3 more
openaire   +2 more sources

EDENet: Elaborate density estimation network for crowd counting

Neurocomputing, 2021
Abstract For the CNN-based density estimation approaches in the field of crowd counting, how to generate a high-quality density map with accurate counting performance and detailed spatial description is still an open question. In this paper, to tackle the aforementioned contradiction, we propose an end-to-end trainable architecture called Elaborate ...
Yinfeng Xia, Yuqiang He, Sifan Peng, Xiaoliang Hao, Qianqian Yang, Baoqun Yin   +5 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
openaire   +1 more source

Fast crowd density estimation with convolutional neural networks

Engineering Applications of Artificial Intelligence, 2015
As an effective way for crowd control and management, crowd density estimation is an important research topic in artificial intelligence applications. Since the existing methods are hard to satisfy the accuracy and speed requirements of engineering applications, we propose to estimate crowd density by an optimized convolutional neural network (ConvNet).
Ce Zhu, Xudong Li, Mao Ye
exaly   +3 more sources

Abnormal crowd density estimation in aerial images

Journal of Electronic Imaging, 2019
The unpreceded growth of intelligent surveillance systems has resulted in an urgent need for automatic analysis of the captured scenes. Automatic detection of an abnormal crowd in aerial images can provide useful information to prevent disasters. In fact, aerial images have the advantage of covering a very large view of the people distributed over a ...
Hazar Mliki, Olfa Arous, Mohamed Hammami
openaire   +1 more source

Density Map Estimation for Crowded Chicken

2019
Intensive breeding is the trend of the breeding industry. In order to make it more convenient to manage and reduce labor costs, sometimes we need to estimate the number of individuals in the poultry farm and discriminate the density distribution to help scientific management. At the same time, crowd density estimation is a developing research direction
Dong Cheng, Tianze Rong, Guitao Cao
openaire   +2 more sources