• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.539-540
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• 2021

In this paper, we consider the management scheme of the crowd group in the sensor networks. In the case of the networks searching the critical area, the operation of crowd group can affect the mission implement. The mobile sink system leading the group networks can change the network configuration as the dangerous data gathered from group sensor nodes. The dynamic network management provides the important role to the mission of mobile sink to react the dangerous environments.

• 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.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.770-778
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• 2007

Fish schooling or group moving in cyber underwater is a part of beautiful and familiar ecosystem. It is not so easy to present the behavior of fish crowd naturally as a computer animation. Thanks to development of computer graphics in entertainment industry, the numbers of digital films and animations is increased and the scenes of numerous crowd are shown to us. Though there are many studies on the techniques to process the behavior of crowd effectively and the developments of crowd behavioral systems, there is not enough study on the development for an efficient crowd behavioral simulator. In this' paper, we smartly present the types offish behavior in cyber underwater and make up for the weak points of time and cost. We develop the fish schooling behavior simulator for the contents of cyber underwater, automating fish behavioral types realistically and efficiently.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.97-105
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• 2014

This study attempts to review the theories and related literatures on crowd funding and build the framework to understand the core concepts of crowd funding. In addition, I explore the applicability of crowd funding platforms for start-ups. For this purpose, I analyze the framework based on the life cycles of projects on crowd funding with the components of stake-holders. Furthermore, I review the results of previous outstanding literature on pros and cons of crowd funding to identify the applicability of crowd funding for start-ups. The results show that the use of crowd funding platform alleviates the risks involved with the information goods which occupy major portion of the projects listed on crowd funding have unique cost structure with high fixed cost and very low variable cost. Consequently, crowd funding is identified as a platform for start-ups of information goods by leveraging the wisdom of crowd. However, crowd funding may not work as an effective platform for start-ups if group thinking emerges. The study provides an implication that it provides a framework for understanding crowd funding and its applicability for start-ups, which can support government's policy for creative economy. Additional empirical research analyzing the data on the projects listed on crowd funding platforms in Korea will be performed in the succeeding study.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.537-538
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• 2021

In this paper, we consider the agent management scheme for the data gathering in the crowd group. To the critical data gathered in dangerous region, the possibility of mission failure caused by the sensor node damage can be high. Hence, we study the node processing to the danger agent node through the cooperative network method for the sensor nodes.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.1-9
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• 2009

In virtual environments, such as computer game and animation, we need to enhance naturalness of crowd simulation. So, we propose a method to generate dynamically moving crowd patterns by applying emotional factors to the individual characters of a crowd in the determination of their behavior. The proposed method mimics human behavior and controls each character in a group to decide its own path according to its individual status. And it is able to generate various moving patterns as a result of letting the individuals go to another group depending upon their conditions. In this paper, some temperament and feeling factors are defined and determination rules for calculating the emotional status are also proposed. Moreover we use a fuzzy theory for accurate representation of the ambiguous expressions such as feeling bad, feeling good and so on. Our experiments show that the suggested method can simulate virtual crowd in more natural and diverse ways.

• Journal of Korea Game Society
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• v.11 no.6
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• pp.193-199
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• 2011

Producing high density crowd simulation is time-consuming task as increasing the number of individuals in the crowds. In this paper, we propose a new control technique that can create realistic high density crowd simulation by using Smoothed Particle Hydrodynamics (SPH) method from fluid simulation field. Equations in SPH method are modified for evacuation, distance maintenance, and group maintenance forces for individual behaviors in the crowds. Experimental results showed that the proposed system could enable natural high density crowd simulation efficiently.

• Journal of Korea Game Society
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• v.19 no.6
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• pp.5-14
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• 2019

In this paper, we propose a modeling and simulation of group behavioral movement of pedestrians using Agent based and Cellular Automata model in intelligent game environment. The social behaviors of the crowds are complex and important, and based on this, the prototype game-model was implemented to show the crowd interaction on AB and CA in the game environment. Our experiment revealed the promise of group behaviour as a cost-efficient, yet accurate platform for researching crowd behaviour in risk situations with real models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.541-542
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• 2021

In this paper, we consider the straggled network treatment in multiple sensor groups. During the moving or the implement of mission, the departed network should be handled. The loss of network group affects the mission implement of overall sensor networks, and it also requests the immediate treatment. In urgent mission environments, the network management of mobile sink should be considered to the group damage.