• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.83-86
• /
• 1996

We propose a mathematical model which describes the walking behavior of a person and to analyze the effect of the personality on the dynamics of the crowd. The fundamental assumption is that the human behavior is not a random process but a deterministic process with several basic mechanisms and each fundamental mechanism is common and only the parameter is different from person to person. The proposed model is based on the servomechanism which drives a person along the planned path from point to point. This model has been applied to simulate the walks of people in a crowd and the simulated results have a good coincidence with actual measurement.

• Proceedings of the Korea Contents Association Conference
• /
• 2008.05a
• /
• pp.10-14
• /
• 2008

Computer-animated crowd scenes are often observed in computer games and feature films. The common way to model locomotion of large human crowds is to employ agent based methods where the behavior of each person is independently modeled. But for large crowds, it is difficult for a user to control all the individuals using individual behavior model. Instead, crowd behaviors can be controlled more intuitively at the group level than at the individual level. In this paper, we present the group force field model to simulate path following behavior for groups. A group is a set of characters who have the same goals, i.e. the same path to follow. We also define three characteristics of grouping behavior: alignment, cohesion, and distribution. Our group force field model preserves these characteristics while avoiding collisions. By using our model, user can generate desired group behaviors from line-up behavior to lumped one.

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

• Journal of Korea Multimedia Society
• /
• v.11 no.10
• /
• pp.1427-1435
• /
• 2008

It is worth it to properly present the behaviors of cyberspace and game characters. It is not so easy to manually supply the actions for all objects one by one, so we need to use crowd animation techniques in order to display automatically, realistically, and effectively. In this paper, we construct a ubiquitous cyber aquarium based on sensors, using the crowd behavior library, which is applied to programming crowd behavior in cyberspace and game applications. We use a sensor board to become aware of a person approaching the cyber aquarium, and according to the perceived distance, the objects in the cyber aquarium automatically react and behave accordingly.

• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.3
• /
• pp.124-131
• /
• 2007

Research field on crowd animation can be classified into two major categories. One is to offer realism of the crowd motion and the other is to improve speed of the animation. For the last decade, a lot of research on realism and behavior of crowd have been presented. But lately, research on improving speed seems like more interesting. Therefore, in this paper, we conducted an experiment to analyze what is the main bottleneck of crowd animation. As the result, we find out one of the most important bottleneck is the number of joints transformed in each animation frame. In order to resolve this problem we propose a novel level-of-detail technique 'motion level-of-detail', which is a joint-reduction technique operated in the pre-processing time. We used a non-linear optimization, SQP (sequential quadric programming), to generate the low detailed motions.

• Journal of the Korea Society of Computer and Information
• /
• v.9 no.3
• /
• pp.87-93
• /
• 2004

In this paper we present a hybrid model that enables dynamic regrouping based on emotion in determining the behavioral pattern of crowds in order to enhance the reality of crowd simulation in virtual environments such as games. Emotion determination rules are defined and they are used for dynamic human regrouping to simulate the movement of characters through crowds realistically. Our experiments show more natural simulation of crowd behaviors as results of this research.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.8
• /
• pp.731-737
• /
• 2014

This paper presents abnormal behavior detection in crowd within surveillance video. We have defined below two cases as a abnormal behavior; first as a sporadically spread phenomenon and second as a sudden running in same direction. In order to detect these two abnormal behaviors, we first extract the motion vector and propose a new descriptor which is combined MHOF(Multi-scale Histogram of Optical Flow) and DCHOF(Directional Change Histogram of Optical Flow). Also, binary classifier SVM(Support Vector Machine) is used for detection. The accuracy of the proposed algorithm is evaluated by both UMN and PETS 2009 dataset and comparisons with the state-of-the-art method validate the advantages of our algorithm.

• International Journal of Computer Science & Network Security
• /
• v.21 no.4
• /
• pp.131-139
• /
• 2021

In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2015.07a
• /
• pp.252-253
• /
• 2015

군중의 이상행동을 검출하는 것은 군중 모니터링, 보안 및 CRM 시스템의 관점에서 중요한 요소 중의 하나이다. 기존의 방법은 대다수가 옵티컬플로우를 기반으로한 검출방법으로 객체가 움직이지 않는 경우에는 객체로 인식할 수 없는 문제점이 생긴다. 또한, 많은 데이터량을 처리하기 때문에 실시간성이 보장되지 않는다는 단점이 있다. 이를 극복하기 위해서, 본 논문에서는 특징점 맵 보정과 분포분석을 통한 군중의 밀집과 대피하는 현상을 검출하는 방법을 제안한다. 먼저, 군중에서 옵티컬플로우 기반으로 움직이는 FAST 특징점을 추출하고 추출된 특징점의 분포에따라 특징점맵을 복원한다. 복원된 특징점 맵과 특징점의 분포에 기반하여 군중의 이상정도를 결정하게 된다. PETS2009 데이터베이스를 사용하여 결과를 측정하였다.

• Fire Science and Engineering
• /
• v.25 no.1
• /
• pp.19-26
• /
• 2011

Korea is rapidly becoming an aging society. As a basic research on increasing evacuation safety design at silver facilities, the study was conducted in consideration of different foot's pace according to the number of seniors and their locations in a crowding of ordinary people and seniors all together. When the seniors were located at the front, the pace reduced to 0.81m/s on average. With 10 seniors which covered 50% of the crowd, the pace decreased to 0.85m/s. It is true that Korea has no existing researches on evacuation behaviour, and functions mentioned in its evacuation safety design is lack of practicality. Therefore, it is certainly necessary to secure any data of the evacuation behavior through various studies on seniors' evacuation behaviors.