Results 231 to 240 of about 40,421 (274)

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 Yılmaz, Siti Norul Huda Sheikh Abdullah, Ven Jyn Kok   +2 more
openaire   +1 more source

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

A novel method for crowd density estimations

IET International Conference on Information Science and Control Engineering 2012 (ICISCE 2012), 2012
Crowd density estimation is important in crowd analysis; this paper proposes a new approach used for crowd density estimation. First, background is removed by using a combination of optical flow and background subtracts methods. Then according to texture analysis, a set of new feature is extracted from foreground image.
null Haiyan Yang, null Hua-An Zhao
openaire   +1 more source

A new approach of crowd density estimation

TENCON 2010 - 2010 IEEE Region 10 Conference, 2010
Crowd density estimation is important in crowd analysis, this paper proposes a new approach used for crowd density estimation. First, background is removed by using a combination of optical flow and background subtract methods. Then according to texture analysis, a set of new feature is extracted from foreground image.
null Wei Li, null Xiaojuan Wu, Koichi Matsumoto, null Hua-An Zhao   +3 more
openaire   +1 more source

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
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Crowd Density Estimation Using Sparse Texture Features

Journal of Convergence Information Technology, 2010
This paper presents a technique for crowd density estimation in surveillance images, which needs neither individual detection and tracking nor a complex training. This is done by building a set of feature templates for different crowd density scenes, and calculating the similarity between templates and features that are extracted from surveillance ...
Nan Dong -, Fuqiang Liu -, Zhipeng Li -
openaire   +1 more source

Estimation of crowd density by counting objects

2017 International Conference on Trends in Electronics and Informatics (ICEI), 2017
People counting is a challenging problem in complex situations. The different problems faced are light intensity, perspective transformation, non-human moving object, shadows, occlusion problem, etc. In this paper, we estimate the number of people with the help of background subtraction and scaling. In the first part, we subtract the current image from
Charul Singh, Mandar Sohani
openaire   +1 more source

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
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   +1 more source

Estimation of crowd density using image processing

IEE Colloquium on Image Processing for Security Applications, 1997
Human beings perceive images through their properties, like colour, shape, size, and texture. Texture is a fertile source of information about the physical environment. Images of low density crowds tend to present coarse textures, while images of dense crowds tend to present fine textures.
Marana, A. N., Velastin, S. A., Costa, L. F., Lotufo, R. A.   +3 more
openaire   +2 more sources