Dissertation > Excellent graduate degree dissertation topics show

The Study on the Model of Generating Behavioral Module on Crowd Animation

Author: WeiLi
Tutor: LiuHong
School: Shandong Normal University
Course: Computer Software and Theory
Keywords: Crowd Animation Particle Swarm Optimization Artificial Bee Colony Algorithm Path Planning
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 98
Quote: 3
Read: Download Dissertation

Abstract


With the rapid development of 3D imaging techniques and simulation technology, computer animation has become an important field of entertainment industry by means of creating a fascinating environment through simulating real scenes. The traditional crowd animation production methods have made many good animations. But with the development of cartoon industry, their limitations are more and more obvious. Because of the universality of crowd behavior in actual world, simulating crowd behavior becomes more and more important in computer animation. Crowd animation has got more and more concerns and becomes a focus of computer graphics and artificial intelligence.Due to the complexity of controlling crowd animation behaviors, generating behavioral module of crowd animation has always been a challenging issue of crowd animation. At present, the problems to be solved in generating behavioral model of crowd animation are mainly as follows:(1) We need to enhance the reality of the paths for crowd animation. The path of movement is generated in crowd animation, so that each individual path meets the rules of group movement and its own individuality, which is an important standard in reliability analysis of crowd animation. It is the prior question that generating behavioral module concerns to avoiding collision and to eliminate intersection between the agent and the nearest obstacle.(2) We need to speed up the generation of crowd animation. In recent years, the research on crowd animation focuses on intelligence and life character of the role. When it is generated, group movement affects real-time rendering greatly because the computation is very big. So how to simulate group motion faster is a universal target.This paper studies the model of generating behavioral module on crowd animation. Firstly, swarm intelligence algorithm is used to plan path for crowd animation in order to enhance the reality and efficiency of crowd animation. Secondly, a method to generate crowd animation with the path data on Maya is designed in order to promote automatic degree in the process of crowd animation design.This paper includes the following aspects: (1) The further research orientation and the swarm intelligent algorithms were clarified by deep understanding the basic principle of crowd animation and analyzing the key problems in designing crowd animation.(2) Suitable optimization algorithm as well as the aspects that needs improving was identified by comparing advantages with disadvantages of some models and methods of evolutionary computation, including particle swarm optimization, ant colony optimization, and artificial bee colony algorithm, etc., and combining the needs of animation designation.(3) It designed the method of collision detection and collision avoidance in crowd movement.(4) The automatic designation of animation path will be realized by considering the optimization process of swarm intelligence algorithms as agents planning the path by themselves on the basis of the method to generate group path automatically by PSO and ABC.(5) A method to generate crowd animation with the path data will be used in order to generate animation automatically.

Related Dissertations

  1. Research on Feature Extraction and Classification of Tongue Shape and Tooth-Marked Tongue in TCM Tongue Diagnosis,TP391.41
  2. Research on Navigation System Related Technology for Moving Objects under Dynamic Environment,TP301.6
  3. Improvement of Ant Colony Algorithmand Its Application in Robot Path Planning,TP242
  4. Active Power Filter and Its Application in Distribution Network,TN713.8
  5. Research on Fuzzy C-Mean Clustering Algorithm Based on Particle Swarm Optimization and Shuffled Frog Leaping Algorithm,TP18
  6. Mobile WSN data collection based on the virtual cluster head Strategy,TP212.9
  7. CAD/CAPP/CAM Integrated System Development for Key Components in Marine Diesel,U664.121
  8. Segmentation of cDNA Microarray Image Using Fuzzy C-means Algorithm Optimized by Particle Swarm,TP391.41
  9. Measuring Extremum Analysis and Path Design of Coordinate Measuring Machine,TH721
  10. Design and Simulation of a Strategy for Backbone Node Deployment in Space Information Networks,TN915.09
  11. The Research on the Target Localization and Tracking Based on WSN,TN929.5
  12. The Design and Implementation of Soccer Robot for RoboCup Middle Size League,TP242
  13. Research on Quantum Particle Swarm Optimization and Its Application to Codebook Design of Image Vector Quantization,TP301.6
  14. Research on Radio Propagation Model Calibration Based on Modified PSO Algorithm,TP18
  15. Improved Binary Particle Swarm Optimization and Its Application in the AGC of Cascade Hydropower Stations,TV737
  16. Urban Traffic Intelligent Control Strategy and Simulation System,U495
  17. Based on particle swarm optimization and control theory ADRC D-STATCOM control system,TM761.1
  18. The Research and Application of Fuzzy Control in HVAC and Room System,TB657.2
  19. City Bus Transfer System Optimization Study and Implementation,U12
  20. Research and Application on Design Resource Dynamic Scheduling Faced to Design Reuse,TB47
  21. Non-probabilistic Reliability Analysis Based on Particle Swarm Optimization and Its Application in Slope Engineering,TB114.3

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile