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    政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 >  Item 140.119/32705
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32705


    Title: 以演化方式模擬人群運動行為
    Simulating Crowd Motion with Evolutionary Computation
    Authors: 王智賢
    Wang, Chih-Chien
    Contributors: 李蔡彥
    Li, Tsai-Yen
    王智賢
    Wang, Chih-Chien
    Keywords: 電腦動畫
    人群運動模擬
    基因演算法
    多代理人系統
    運動隊伍組態
    computer animation
    crowd motion simulation
    genetic algorithm
    Multiple Agent System
    Motion Formation
    Date: 2005
    Issue Date: 2009-09-17 14:05:57 (UTC+8)
    Abstract: 近年來,在電腦動畫的應用中,虛擬人群模擬的需求越來越多;但人群運動的模擬對於動畫設計師而言,仍是一件十分繁瑣耗時的工作。過去有許多研究曾以虛擬力場模擬簡單的生物群聚行為,但所模擬出的動畫品質與虛擬力場的參數及虛擬環境息息相關,因此經常需要以人工的方式耗時地調整出適當的虛擬力場參數。因此,我們提議以此問題定義成一個基因演算法的問題,針對不同的移動行為,定義適切的適應函數,再由系統根據不同環境自動演化出適當的虛擬力權重組合,以供產生不同人群移動行為之動畫時參考。在本篇論文中,我們已完成基因演算法的設計及人群動畫模擬系統,並設計了不同的典型環境進行電腦模擬實驗,以驗證此方法的可行性。
    The demands for virtual crowd simulation have been increasing in recent years but creating realistic crowd motions remains a complex and time-consuming task for a computer animator. In the literature、much work has been proposed to use virtual forces to simulate the motion of a group of virtual creatures such as birds and fishes. However、the quality of the simulations largely depends on the weights of the component virtual forces as well as the scene where the agents are situated. Usually it requires the animator to tune these parameters for a specific scene in order to obtain the desired result. In this thesis、we propose to use genetic algorithm to generate an optimal set of weighting parameters for composing virtual forces according to the given environment and desired movement behavior. We have implemented the proposed genetic algorithm as well as the crowd simulation system. Extensive experiments have also been conducted to study the effects of typical scenes and behaviors on the parameter sets and verify the feasibility of the approach.
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    Description: 碩士
    國立政治大學
    資訊科學學系
    90750322
    94
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0907530222
    Data Type: thesis
    Appears in Collections:[資訊科學系] 學位論文

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