• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3769-3789
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• 2018

Social pedestrian groups are the basic elements that constitute a crowd; therefore, detection of such groups is scientifically important for modeling social behavior, as well as practically useful for crowd video understanding. A social group refers to a cluster of members who tend to keep similar motion state for a sustained period of time. One of the main challenges of social group detection arises from the complex dynamic variations of crowd patterns. Therefore, most works model dynamic groups to analysis the crowd behavior, ignoring the existence of stationary groups in crowd scene. However, in this paper, we propose a novel unified framework for detecting social pedestrian groups in crowd videos, including dynamic and stationary pedestrian groups, based on spatiotemporal-oriented energy measurements. Dynamic pedestrian groups are hierarchically clustered based on energy flow similarities and trajectory motion correlations between the atomic groups extracted from principal spatiotemporal-oriented energies. Furthermore, the probability distribution of static spatiotemporal-oriented energies is modeled to detect stationary pedestrian groups. Extensive experiments on challenging datasets demonstrate that our method can achieve superior results for social pedestrian group detection and crowd video classification.

• Journal of the Society of Disaster Information
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• v.7 no.1
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• pp.12-20
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• 2011

This study was performed for identifying the characteristics of mass gathering and human injury in mass gathering based on the literature survey and analysis of mass gathering and crowd packing. The size and density of crowd influenced the characteristics of mass gathering according to type of mass gathering. The variables and causes of human injuries of mass gathering have positive or negative influences based on the weather, attendance, duration, location, mobility, event type, crowd mood, alcohol, drug, crowd density and age. Based on the physical mechanism of crowd packing, the degree of crowd packing was influenced by crowd pressure, crowd density and lasting time. But the magnitude of pressure for pedestrian injury criteria remains for further research.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1104-1114
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• 2014

In large-scale crowd simulations, it is very important for the decision-making system of manipulating interactive behaviors to minimize the computational cost for controlling realistic behaviors such as collision avoidance. In this paper, we propose a large-scale realtime crowd simulation method using the affordance and navigation potential fields such as attractive and repulsive forces of electromagnetic fields. In particular, the model that we propose locally handles the realistic interactions between agents, and thus radically reduces the cost of expensive computation on interactions which has been the most problematic in crowd simulation. Our method is widely applicable to the expression and analysis of various crowd behaviors that are needed in behavior control in computer games, crowd scenes in movies, emergent behaviors of evacuation, etc.

• Journal of Korean Society of Disaster and Security
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• v.16 no.1
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• pp.49-60
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• 2023

After the 10.29 Itaewon disaster, interests in the crowd crush injury increased, but it is pointed out that the academic and practical basis related to crowd crush is still weak in Korea. Therefore, in this study, terms and concepts related to crowd crush were investigated and proposed, and representative cases of crowd crush events were investigated and summarized. Approaches based on representative cases were investigated, and among them, video analysis, simulation, questionnaire survey and interview methods were derived as an essential approach methods. Through this research, it is expected that standardization of Korean terminology, concept establishment, evaluation, and systematization of approach methods of crowd crush can be accomplished.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.26-34
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• 2024

Most human emotions are conveyed through facial expressions, which represent the predominant source of emotional data. This research investigates the impact of crowds on human emotions by analysing facial expressions. It examines how crowd behaviour, face recognition technology, and deep learning algorithms contribute to understanding the emotional change according to different level of crowd. The study identifies common emotions expressed during congestion, differences between crowded and less crowded areas, changes in facial expressions over time. The findings can inform urban planning and crowd event management by providing insights for developing coping mechanisms for affected individuals. However, limitations and challenges in using reliable facial expression analysis are also discussed, including age and context-related differences.

• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.87-95
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• 2023

On October 29, 2022, a very large number of people gathered in Itaewondong, Yongsan-gu, Seoul, Korea for a Halloween festival, and as crowds pushed through narrow alleys, 159 deaths and 195 injuries occurred, making it the largest crushing incident in Korea. There have been a number of stampede deaths where crowds gathered at large-scale festivals, event venues, and stadiums, both at home and abroad. When the density increases, the physical contact between bodies becomes very strong, and crowd turbulence occurs when the force of the crowd is suddenly added from one body to another; thus, the force is amplified and causes the crowd to behave like a mass of fluid. When crowd turbulence occurs, people cannot control themselves and are pushed into he crowd. To prevent a stampede accident, investigation and management of areas expected to be crowded and congested must be systematically conducted, and related ministries and local governments are planning to establish a crowd management system to prepare safety management measures to prevent accidents involving multiple crowds. In this study, based on national data, a continuous digital topographic map is modeled in 3D to analyze the risk of crowding and present a plan for selecting high-risk walking routes. Areas with a high risk of crowding are selected in advance based on various data (numerical data, floating population, and regional data) in a realistic and feasible way, and the analysis is based on the visible results from 3D modeling of the risk area. The study demonstrates that it is possible to prepare measures to prevent cluster accidents that can reflect the characteristics of the region.

• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.96-103
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• 2023

Generally, human stampedes and crowd collapses occur when people press against each other, causing falls that may result in death or injury. Particularly, crowd accidents have become increasingly common since the 1990s, with an average of 380 deaths annually. For instance, in Korea, a stampede occurred during the Itaewon Halloween festival on October 29, 2022, when several people crowded onto a narrow, downhill road, which was 45 meters long and between 3.2 and 4 meters wide. Precisely, this stampede was primarily due to the excessive number of people relative to the road size. Essentially, stampedes can occur anywhere and at any time, not just at events, but also in other places where large crowds gather. More specifically, the likelihood of accidents increases when the crowd density exceeds a turbulence threshold of 5-6 /m². Meanwhile, festivals and events, which have become more frequent and are promoted through social media, garner people from near and far to a specific location. Besides, as cities grow, the number of people gathering in one place increases. While stampedes are rare, their impact is significant, and the uncertainty associated with them is high. Currently, there is no scientific system to analyze the risk of stampedes due to crowd concentration. Consequently, to prevent such accidents, it is essential to prepare for crowd disasters that reflect social changes and regional characteristics. Hence, this study proposes using digital topographic maps and crowd-density risk simulations to develop a 3D model of the region. Specifically, the crowd density simulation allows for an analysis of the density of people walking along specific paths, which enables the prediction of danger areas and the risk of crowding. By using the simulation method in this study, it is anticipated that safety measures can be rationally established for specific situations, such as local festivals, and preparations may be made for crowd accidents in downtown areas.

• The Journal of the Korea Contents Association
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• v.17 no.6
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• pp.643-649
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• 2017

This research is to compare factors which influence to mobilize police force necessary for crowd gathering occasions, and the purpose of this research is to prepare scientific basis for mobilization of police force by understanding order of priority of obstructive factors to mobilize police force for progressing safe crowd gathering occasions. Crowd gathering occasion has a characteristic that minor cause can lead to huge damage because many people concentrically gather at a specific place. In order to control these risks, it is necessary to analyze criteria on order of priority which can arouse risk to mobilize police force. In this research, I classified the factors influencing safety of crowd gathering occasion as internal risk factor, external risk factor and traffic safety threatening and set up the level of private security manpower and participants mobilized to crowd gathering occasion as independent variable and set up mobilized police force from 2013 to 2014 as dependent variable and analyzed it hierarchical analysis. From the result of analysis, the biggest influence to mobilization of police force for crown gathering occasion was the number of participants, and next self order-keeping agents and reason of mobilizing police force. Based on the result of analysis that the biggest factor to mobilize police force to crowd gathering occasion is the number of participants, it can be resulted that the number of participants influence to the risk of crowd gathering occasion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.912-928
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• 2019

Crowd behavior analysis research has revealed a central role in helping people to find safety hazards or crime optimistic forecast. Thus, it is significant in the future video surveillance systems. Recently, the growing demand for safety monitoring has changed the awareness of video surveillance studies from analysis of individuals behavior to group behavior. Group detection is the process before crowd behavior analysis, which separates scene of individuals in a crowd into respective groups by understanding their complex relations. Most existing studies on group detection are scene-specific. Crowds with various densities, structures, and occlusion of each other are the challenges for group detection in diverse crowded scenes. Therefore, we propose a group detection approach called Collective Interaction Filtering to discover people motion interaction from trajectories. This approach is able to deduce people interaction with the Expectation-Maximization algorithm. The Collective Interaction Filtering approach accurately identifies groups by clustering trajectories in crowds with various densities, structures and occlusion of each other. It also tackles grouping consistency between frames. Experiments on the CUHK Crowd Dataset demonstrate that approach used in this study achieves better than previous methods which leads to latest results.

• Asia pacific journal of information systems
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• v.26 no.1
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• pp.109-123
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• 2016

The success of a crowd-funding project can be attributed to various reasons, among which, backer's (also known as 'investor', or 'funder') perception of project credibility may be a salient one. The purpose of this study is to investigate the extent to which perceived project credibility can affect a backer's investment decision. We examine the factors that could influence the building of perceived project credibility by testing the proposed research model using survey data. Analysis results indicate that perceived project credibility has a significantly positive effect on backer's investment intention. Furthermore, information quality and source credibility are two key determinants of perceived project credibility. This study contributes to crowd-funding literature by enriching the list of successful factors for fund-raising with project credibility. The study also has practical implications because it explains why and how a backer's perception of project credibility can be improved.