基于樣例的動畫角色多樣化研究
發(fā)布時間:2018-07-05 02:29
本文選題:動畫角色 + 模型融合。 參考:《合肥工業(yè)大學(xué)》2011年碩士論文
【摘要】:基于樣例的快速建模方法一直是計算機(jī)3D建模領(lǐng)域的熱點(diǎn)研究方向之一,將樣例建模引入動畫角色三維模型多樣化創(chuàng)作及展示中,在動漫影視、3D游戲等領(lǐng)域存在著大量需求。本文在對樣例建模研究的廣泛調(diào)研基礎(chǔ)上,針對動畫角色模型的特點(diǎn),分別從模型融合和微變形兩個角度探索實(shí)現(xiàn)角色模型的多樣化生成,研究兩種方法各自的應(yīng)用范圍和算法特點(diǎn),并在此基礎(chǔ)上,建立動畫角色的模型多樣化隨機(jī)生成系統(tǒng),最后給出了多樣化角色場景的自動生成效果。 本文的主要工作包括以下幾個方面: (1)針對低精度模型頂點(diǎn)稀疏和廣泛使用貼圖表現(xiàn)的特點(diǎn),提出了一種基于簡化調(diào)和映射的方法提高網(wǎng)格融合的效率,并利用貼圖合成技術(shù)保留了源模型貼圖的內(nèi)容并生成過渡貼圖內(nèi)容,保證了新生成模型的完備性,在3D模型的數(shù)據(jù)重用和多樣化上具有重要的意義。 (2)根據(jù)動畫及游戲領(lǐng)域?qū)ν惤巧鄻踊囊?同時滿足對時空復(fù)雜度的嚴(yán)格限制,提出了基于微變形的多樣化模型生成方法。利用參考式變形和路徑式變形等微變形方法生成“主體相同,細(xì)節(jié)各異”的新模型,在保證算法的執(zhí)行效率和代價基礎(chǔ)上,豐富場景中的角色形態(tài)。 (3)在前述研究工作的基礎(chǔ)上,實(shí)現(xiàn)了動畫角色的模型多樣化隨機(jī)生成系統(tǒng)。首先,建立參數(shù)模式庫來存儲滿足條件的多樣化參數(shù)模式集合。其次,根據(jù)場景需求并輔以隨機(jī)的方式批量載入?yún)?shù)模式集。最后,根據(jù)參數(shù)模式中完備的參數(shù)信息完成對多樣化結(jié)果的解析和復(fù)現(xiàn),并自動生成滿足要求的多樣化動畫角色場景。
[Abstract]:The fast modeling method based on sample has been one of the hot research directions in the field of computer 3D modeling. There is a great deal of demand in the field of animation film and television 3D game to introduce sample modeling into the creation and display of 3D model of animation characters. In this paper, based on the extensive research on the modeling of the sample, according to the characteristics of the animation role model, this paper explores the diversification of the role model from the perspective of model fusion and micro-deformation. Based on the study of the application scope and algorithm characteristics of the two methods, a model diversification random generation system for animation roles is established. Finally, the automatic generation effect of the diverse role scenes is given. The main work of this paper includes the following aspects: (1) aiming at the characteristics of low precision model vertex sparse and widely used map representation, a method based on simplified harmonic mapping is proposed to improve the efficiency of mesh fusion. The content of the source model map is preserved and the transitional map content is generated by using the mapping composition technique, which ensures the completeness of the newly generated model. It has important significance in data reuse and diversification of 3D model. (2) according to the requirements of animation and game field for the diversification of similar characters, it meets the strict limitation of space-time complexity. A method for generating diversified models based on micro deformation is proposed. A new model with the same subject and different details is generated by using the methods of reference deformation and path deformation, which can ensure the efficiency and cost of the algorithm. (3) on the basis of the previous research work, the model diversification random generation system of animation characters is realized. First of all, a parameter schema library is established to store a variety of parameter pattern sets that satisfy the conditions. Secondly, the parameter pattern set is loaded in batches according to the requirements of the scene and in a random manner. Finally, according to the complete parameter information in the parameter mode, the analysis and reproduction of the diversified results are completed, and the multi-character scene of the animation is generated automatically.
【學(xué)位授予單位】:合肥工業(yè)大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2011
【分類號】:TP391.41
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