Results 1 to 10 of about 4,521,340 (293)
A COMPARATIVE STUDY OF CROWD COUNTING AND PROFILING THROUGH VISUAL AND NON-VISUAL SENSORS [PDF]
Acta Informatica Malaysia, 2019 In this paper we present a comparative critical study of visual and non-visual sensors used in crowd behavior analysis. The understanding of crowd has main impact of the analysis how much they support the system is the key factor of the analysis.
Jugal Kishor Gupta, S.K. Gupta
doaj +1 more source
AVMSN: An Audio-Visual Two Stream Crowd Counting Framework Under Low-Quality Conditions
IEEE Access, 2021 Crowd counting is considered as the essential computer vision application that uses the convolutional neural network to model the crowd density as the regression task.
Ruihan Hu +8 more
doaj +1 more source
Crowd Counting with Density Adaption Networks
CoRR, 2018 Crowd counting is one of the core tasks in various surveillance applications. A practical system involves estimating accurate head counts in dynamic scenarios under different lightning, camera perspective and occlusion states. Previous approaches estimate head counts despite that they can vary dramatically in different density settings; the crowd is ...
Li Wang 0033 +5 more
openaire +3 more sources
Three-dimensional atrous inception module for crowd behavior classification
Scientific ReportsRecent advances in deep learning have led to a surge in computer vision research, including the recognition and classification of human behavior in video data.
Jong-Hyeok Choi +3 more
doaj +1 more source
HAGN: Hierarchical Attention Guided Network for Crowd Counting
IEEE Access, 2020 In recent years, deep learning based crowd counting networks have achieved significant progress. However, most of them generate rough crowd density maps due to low-resolution features used for estimating crowd distribution, which affects the performance ...
Zuodong Duan, Yujun Xie, Jiahao Deng
doaj +1 more source
Large-Scale Station-Level Crowd Flow Forecast with ST-Unet
ISPRS International Journal of Geo-Information, 2019 High crowd mobility is a characteristic of transportation hubs such as metro/bus/bike stations in cities worldwide. Forecasting the crowd flow for such places, known as station-level crowd flow forecast (SLCFF) in this paper, would have many benefits ...
Yirong Zhou +5 more
doaj +1 more source
Cascaded Multi-Task Learning of Head Segmentation and Density Regression for RGBD Crowd Counting
IEEE Access, 2020 In this paper we propose a novel regression based RGBD crowd counting method. Compared with previous RGBD crowd counting methods which mainly exploit depth cue to facilitate person/head detection, our approach adopts density map regression and is more ...
Desen Zhou, Qian He
doaj +1 more source
Visual influence networks in walking crowds
Journal of the Royal Society InterfaceAbstract Collective motion in animal groups emerges from local visual interactions, but the network structure underlying human crowd dynamics remains unexplored. Here, we develop a method to reconstruct dynamic visual influence networks from motion-capture data on walking human crowds, using the time-dependent delayed directional ...
Kei Yoshida +2 more
openaire +1 more source
Learning Multi-Level Features to Improve Crowd Counting
IEEE Access, 2020 Crowd counting is a task that aims to estimate the number of people in an image. Recent crowd counting methods make significant progress by employing convolutional neural networks to regress crowd density maps.
Zhanqiang Huo +4 more
doaj +1 more source
Biologically Inspired Neural Networks for Crowd Escape Detection in Complex Scenes [PDF]
Jisuanji gongchengCrowd escape behavior in public places is highly likely to cause serious public safety disasters. Traditional computer vision technology can detect a few characteristics of crowd escape behavior, but it is difficult to face complex dynamic visual scenes.
FENG Tao, HU Bin, XU Guangyuan
doaj +1 more source