Results 251 to 260 of about 4,036,534 (282)

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

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

Crowd density estimation: An improved approach

IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, 2010
Crowd density estimation is important in crowd analysis and texture analysis is an efficient method to estimate crowd density, this paper proposes an improved estimation approach based on texture analysis. First, background is removed by using a combination of optical flow and background subtract method. Then according to texture analysis, a set of new
Wei Li, Xiaojuan Wu, Koichi Matsumoto, Hua-An Zhao   +3 more
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

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
openaire   +1 more source

Crowd Density Estimation Based on Convolutional Neural Network

2020 IEEE 20th International Conference on Communication Technology (ICCT), 2020
For tasks like crowd density estimation and crowd counting, the model needs a larger receptive field. The easiest way to obtain a large receptive field is to use a large convolution kernel, which increases the model's parameters. Therefore, to realize a large receptive field, the model parameters are not excessive and the model performance is not bad ...
Zehui Zhang, Xuehong Sun
openaire   +1 more source

Deep Learning Framework for Density Estimation of Crowd Videos

2018 8th International Symposium on Embedded Computing and System Design (ISED), 2018
Estimation crowd density from surveillance video is a significant research filed in the area of computer vision. Crowd density is one of the critical crowd monitoring parameters which can represent the space that is possessed by the crowd in the scene under surveillance.
Muhammed V. Anees, G. Santhosh Kumar
openaire   +2 more sources

Auto-Encoders for Crowd Density Estimation

2022 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), 2022
Kashika Akhouri, Samya Jain, Tanya Chhikara, Ritu Rani, Poonam Bansal, Arun Sharma 0002   +5 more
openaire   +2 more sources

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   +2 more sources

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 0002   +3 more
openaire   +1 more source