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The accuracy of camera calibration depends significantly on the control point detection which customarily subjects to image noise, distortion and resolution. This paper uses concentric circle grids as the calibration pattern and accordingly proposes a robust and accurate control point detection method for camera calibration. Each set of concentric circles on the grids pattern consists of multiple circles whose radii decrease progressively. The geometric structure of multi-hierarchies can not only robustly extract control points from complicated scenarios but also build a voting scheme to avoid numerical instability resulting from the estimation of projected centers. According to the common self-polar triangle of concentric circles and the local sub-pixel edge detection algorithm, we efficiently estimated sub-pixel coordinates of control points under projective transformation. Simulations and real experiments were conducted to demonstrate that the performance of calibration using concentric circle grids is superior to the popular grid patterns with respect to the image noise, distortion and resolution.

Mass incidents pose a serious threat to public order and national security, building a knowledge base in the field of mass incidents, visualizing the relationship between entities from incidents, and scientifically reasoning about key information about incidents have become key links in effectively responding to mass violence crimes. In view of the lack of existing mass incident knowledge graph analysis methods and strong subjective reasoning methods, based on the BiLSTM-CRF model, this paper analyzes event elements and entity associations by extracting entities from the text data of mass events, the protege software is used to construct the mass event ontology model, and the visualization of the mass event knowledge graph is realized based on the neo4j graph database. The research results show that the knowledge graph established in this paper can better reflect the correlation between the elements in the mass incident, and is of great significance to the national security department to improve the emergency decision-making ability.

Based on the development technology of WebGIS, the mobile terminal is accessed through the public mobile communication network, a cross-regional visual command and dispatch communication platform is set up. The platform can realize police officers' real-time location display, track replay and optimal path planning. At the same time, the platform integrates the Web instant messaging functions with geographic information system, and it can directly operate the target on the map to achieve more convenient and efficient command and dispatch functions. With the excellent regional coverage of the public mobile communication network, the platform can achieve cross-regional staff dispatching missions. The use of visual command and dispatch communication platform can effectively utilize the current limited manpower and material resources in emergency situations and maximize the capability of emergency handling and provide effective solution for cross-regional emergency command and dispatch tasks.

This paper mainly proposed a kind of algorithm based on moving object detection and direction recognition, with a variety of data in video surveillance system, constructing a moving objects trajectories system with a combination of artificial and video surveillance system, to find escape routes of suspects accurately and make work easy for investigators. This system was created by Python language, MySQL database language and Open CV direction recognition technology, completing usage of map, creating database structure and recognizing the direction of a moving object, to predict object moving direction.

At present, a person-specific 3D model generation technology has been an active research topic for scientists in the field of computer vision and computer graphics. The paper proposes a 3D modeling method based on single photograph, by analysis of individual difference like geometric features which present the shape and locations of facial components. An extension of the basic Active Appearance Model is proposed to localize some facial feature points in the frontal image and all these feature points are aligned to fit the generic 3D face model to a specialized one to reflect the given person's face, being both more robust and faster. Then an optimized texture mapping of cylindrical projection and model adjustment technologies are presented, to synthesize personal virtual face realistically. This method rectifies these previous defects, such as the difficulty in gaining access to acquiring the accurate data of a 3D face model, slowly manual location methods, incomplete facial information mining. The approach gives a significant improvement in both the reliability and the overall accuracy of 3D modeling.

This paper uses Agent-based modeling and simulation to study collective violent events from the perspective of individual's risk perception, by abstracting individual's risk preference, emotion factor, risk level and other factors we analyze and explore the influence of each factors to collective violent events. Considerable simulations indicate that, individual's density risk preference determines assemble morphology of the crowd and the event-relevance and emotion factor together determine the trend of events, while police's timely and effective intervention could prevent the spreading of the events. These conclusions provide meaningful theoretical basis for relevant organs.

This paper uses the method of Agent-Based Modeling and Simulation to analyze the interactions among participants in Mass Violence Events. We study the affection degree of instigators, activists, cops and civilians to individual civilians to attend the events. The results show that the influencing factors which could affect civilians to attend the events are agitation power, number of activists, number of cops and risk-avoidance and so on. It shows that the law of development of Mass Violence Events. These results could provide public security organs with some certain theoretical support.

This paper uses base-Agent method to build a new model of researching the evolution of discontent in mass violence event, in which model we introduce emotion factor, relation factor, risk factor and relevance factor as the attribute value of the individual Agent, then using psychophysics’ correlation theory to quantize the change of individual discontent. In the paper, by setting different initial values, we make relevant experiments to study the process of evolution of discontent of a typical mass violence event that has happened and three other different circumstances. All of what we achieved from this paper can offer help to the police to understand the inherent mechanism and law of mass violence event, also can provide guide for taking pointed measures to prevent and manage mass violence event.

This paper presents an agent-based collective model to study “non-organization and direct interest” collective events. The purpose of this model is to analyze the spread phenomenon emerging in this type of events and explain some important characters which affect the spread. The experimental results show that the degree of spread is influenced by some variables, and these variables also influence individual's motion intensity. Simulations reproduce the spread phenomenon of this type of events and indicate the weight of different factors which impact on individual's motion intensity, revealing the regular pattern of this event.

This paper introduces a new method for analyzing Mass Violence Events, and then we make use of Intelligent Artificial and Agent-Based System to deal with them. In the meanwhile, we describe and defy three kinds of agents (cops, activists and civilians), what comes next is that we apply these theories to model and simulate such events. The simulation results show that the behaviors of activists can easily affect whether civilians will join into Mass Violence Events, if they attend events, it will lead cops to face more difficulties when dealing with them. The new method can provide certain theoretical meanings for public security organs to address Mass Violence Events.

To formulate a reasonable and effective urban seismic traffic evacuation plan, this paper applied modified equivalent length, analysis of the factors which influence the seismic evacuation process, using the improved equivalent length to instead of the actual road network, this paper put forward an improved seismic evacuation dynamic traffic assignment model which is based on CTM. Experimental results show that the model can either be multiple origin-destination network optimization problem simplified into single origin-destination traffic assignment network optimization problem, and can be properly reflected the dynamic characteristics of the evacuation traffic flow, and can be satisfied the dynamic allocation demand of traffic evacuation simultaneously.

Before city emergencies happen, one of the most important tasks is to develop contingency plans, and reasonable analysis of space evacuation vulnerability is an important part of contingency plans. Based on the analysis of evacuation vulnerability of emergency area, this article develops a critical evacuation cluster model, and searches for the critical cluster of evacuation area by heuristic searching algorithm. At the end of the article, it generates the maps of space evacuation vulnerability in city emergency with the technology of GIS, which provide technical support for the making of contingency plans of city emergency.

This paper bases on the research of cellular automaton and Agent, proposing a Grid-Agent model. This model uses the grid as the basic unit, and the individual Agents in the grid implement their movement by judging the state of their own and the grid around to achieve the purpose of simulating the crowd behavior. This will overcome the insufficient of the cellular automaton by simulating the crowed behavior, and also overcome shortcomings that the lack of temporal logic the Agent-based. At last, this paper simulates the crowd-gathered behavior by using the model, and the results show that the Grid-Agent model is more accurate and logic in the simulation of human behavior, and we can observe and research the regulation of crowd-gathered behavior better.

During any extreme event, especially the evacuation in crowded places. The keys to saving lives are orderly and efficient evacuations. We have improved the traditional particle swarm optimization. It can simulate non-adaptive crowd behavior in the crowd facilities during the emergency evacuation. We introduce the concept of the leader (trained staff) and the parameter of influence, and analyzed the influence of the leader on the evacuation process, especially the factors of the leader's distribution, number and influence. It will provide theoretical support for the evacuation of High-density facilities.

This paper studied the regulation of mass event from the perspective of its individual, and proposed an agent-based mass event modeling. The individual behavior of aggregation, riots, fled in mass event was modeled. Then the model was applied to computer simulation for observing crowd behavior of all the individuals in the three states. By this, we can study the behavior rules of mass event.

This paper puts forward a method based on Logistic regression of emergency evacuation traffic trip generation forecasting model. Based on analysis of Xiamen residents earthquake evacuation survey data, the software of applied statistic SPSS could establish emergency evacuation traffic trip generation forecasting model by Logistic regression. This model could predict the probability of all evacuation modes of residents to obtain the better emergency processing plan of traffic evacuation in earthquake disasters. Subsequently, for the purpose of making the more reasonable and effective of city emergency management plan, the test sample would be simulated to accuracy and fitting degree of the prediction model result.

When city emergencies happen, one of the most important tasks of emergency rescue is to find the shortest path to the emergency in shortest time, scientific and rational path plays an important role in improving rescue efficiency. According to the needs of city emergency rescue and basing on the analysis of the classical algorithm for solving the shortest path problem (Dijkstra algorithm), this article discusses an improved algorithm within dynamic restricted searching area which dynamically changes the direction of the search and restricts the searching area. This new method reduces time and space complexity and improves the efficiency of the algorithm. At the end of the article, it improves the practicality and reliability of this improved algorithm by simulation.

During and after any extreme event of natural or man-made origin, the primary objectives are getting people out of harms way and to an safety area. The keys to saving lives are orderly and efficient evacuations. We have proposed a new model based on the traditional lattice gas automate, in our paper, it can simulate the human crowd behavior in the crowd facilities, such as shopping malls, stadiums, school buildings etc, under the condition that many people rush to exits at the same time. In this model, people move by their instinct and the information what they obtained. In order to reappearance the scenes of the events and reach a better evacuation. We introduce psychological factors, velocity levels of pedestrians and exit levels in our model.

On the basis of the characters of footprint shape, a toe shape description method based on geometric characteristic values of toe image is proposed. Corner detection is carried out on toe region, and the characteristic points which can describe the toe shape are confirmed by the edge of toe image. Through finding characteristic points whose distances to the center are stable and which can distinguish different toe shapes and the correlation among them, the toe shape characteristic vector is built. On the basis of toe shape characteristic vector, a toe shape recognition method based on fuzzy neural networks is proposed. Firstly, according to the statistical distribution disciplinarians of different shape toe images, membership functions are constructed respectively from the angle, length and region parameters, and these values are used as single judgment factors. The comprehensive judgment vector can be obtained through the operation among these single judgment factors. At last, the distance vector between comprehensive judgment vector and four model vectors are computed to feed into neural networks in order to judge. Because the method based on fuzzy neural network can reflect subjectively and correctly the different shapes of toe image, so the total automatic recognition rate amounts to 92.80%.

A feature-level image fusion method based on segmentation region and neural networks is proposed in this paper. Firstly, the source images are segmented and merged into a set of common regions which are used for guiding the whole fusion process; then selecting the corresponding segmentation regions from the source images respectively and extracting features representing clarity in the two regions; at last the features are fed into a neural networks to judge clear region to reconstruct the final fusion image. The experimental results show that the fusion effect is better.

The estimation of harmonic to noise ratio (HNR) in transmitted sound signals with a wavelet transform was proposed. When subjects phonate sustained vowels in breathy, falsetto, leakage and pressed mode in normal loudness, the HNR in the human voice and transmitted sound signals was estimated and compared. The results indicated that the HNR in transmitted sound signals could accurately image vocal fold vibration characteristics. It would be a useful measurement for clinical laryngeal disease diagnosis.