Results 241 to 250 of about 105,553 (280)

Abnormal High-Density Crowd Dataset

2020 Fourth International Conference on Multimedia Computing, Networking and Applications (MCNA), 2020
Anomaly detection within crowded environments is a key challenge in the computer vision and crowd behaviour understanding fields. Furthermore, anomaly detection within high-density crowds remains an insufficiently explored area. In this paper, we propose a novel abnormal high-density crowd dataset.
Samar Mahmoud, Yasmine Arafaf
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Crowd Density Analysis and tracking

2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2015
Crowd Density Analysis (CDA) aims to compute concentration of crowd in surveillance videos. This paper core is to estimate the crowd concentrations using crowd feature tracking with optical flow. Local features are extracted using Features for Accelerated Segment Test (FAST) algorithm per frame.
P.V.V. Kishore, R. Rahul, K. Sravya, A.S.C.S. Sastry   +3 more
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Crowd Density Teller using Infrared Technology

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2021
The proposed paper aims to provide a solution for people gathering and help to maintain social distancing in the era of novel coronavirus. Especially, people who are health conscious will get a sovereign remedy from being infected. This invention will count and show the number (on the online platform) of persons present at any outlet or surrounded ...
Manisha Pant, Rajat Parashar, Reshu Agarwal, Alka Chaudhary, Shylaja VinayKumar Karatangi   +4 more
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Density estimation in crowd videos

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
In crowd surveillance systems, it is important to select the proper analysis algorithm considering the properties of the video content. The inappropriate algorithm selection may result in performance degradation and generation of false alarms. An important feature of crowd videos is the density of the crowd.
Ayse Elvan Gunduz, Tugba Taskaya Temizel, Alptekin Temizel   +2 more
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LITERATURE REVIEW ON CROWD COUNTING AND CROWD DENSITY MAPPING METHODOLOGIES

International Journal of Engineering Applied Sciences and Technology, 2021
Purpose of Review: Artificial Intelligence and Machine Learning technologies have enabled the analysis of the crowd which helps monitor and manage the crowd effectively. With further advancements in the field of AI and ML, the quality and the accuracy of the analysis have improved considerably.
Bhat Sirish Mahadeva, Chandan C Rao, Thushar S Kulal, Udbhav U, Ranganatha K   +4 more
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Density Avoidance in Pedestrian Crowds

Proceedings of the 8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS), 2015
Traffic jam caused by self-propelled particles is a research topic of broad interest. Cellular automata models are used for the simulation and analysis. One of the popular models is the floor field model. We add the rule of avoiding high density among particles to the model and show that it enables simulating a more realistic situation.
Daichi Maruyama, Tatsuji Takahashi
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Density constraints for crowd simulation

2009 International IEEE Consumer Electronics Society's Games Innovations Conference, 2009
Virtual worlds are nowadays commonly used in interactive applications, like computer games and simulations. Typically, such worlds are populated by a large number of virtual characters. On one hand, these characters have global goals with respect to the environment and thus, they must be able to plan their paths toward their desired locations.
Karamouzas, I., Bakker, J., Overmars, M.H.   +2 more
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Population density, crowding and human behaviour

Progress in Human Geography, 1979
The author reviews the existing literature on density and crowding from a geographical perspective with a focus on the concerns of urban geographers. Several types of empirical studies are described and reviewed and research on models of crowding is outlined (ANNOTATION)
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Multiple human tracking in high-density crowds

Image and Vision Computing, 2009
In this paper, we present a fully automatic approach to multiple human detection and tracking in high density crowds in the presence of extreme occlusion. Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion.
Irshad Ali, Matthew N. Dailey
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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
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