基于運(yùn)動(dòng)圖的運(yùn)動(dòng)合成方法研究
發(fā)布時(shí)間：2018-08-29 18:33
【摘要】： 虛擬人運(yùn)動(dòng)合成技術(shù)一直是虛擬現(xiàn)實(shí)領(lǐng)域研究的難點(diǎn)和熱點(diǎn)之一,也是數(shù)字文化產(chǎn)業(yè)的核心技術(shù)之一,該技術(shù)在影視動(dòng)漫、三維游戲、安全預(yù)演等諸多領(lǐng)域具有廣闊的應(yīng)用前景。在這些應(yīng)用中不僅要求逼真的運(yùn)動(dòng)效果,而且要求能夠靈活的控制虛擬人運(yùn)動(dòng)。本文針對(duì)這些應(yīng)用需求,深入研究了基于運(yùn)動(dòng)圖的運(yùn)動(dòng)合成方法,從運(yùn)動(dòng)圖的數(shù)據(jù)準(zhǔn)備、運(yùn)動(dòng)圖的構(gòu)建以及運(yùn)動(dòng)圖的應(yīng)用三方面展開(kāi),取得的主要研究成果如下: 一、在運(yùn)動(dòng)圖的數(shù)據(jù)準(zhǔn)備階段,提出了一種基于特征的人體運(yùn)動(dòng)捕獲數(shù)據(jù)自動(dòng)分割方法。 對(duì)運(yùn)動(dòng)捕獲數(shù)據(jù)進(jìn)行合理的分割是構(gòu)建運(yùn)動(dòng)圖的前提和基礎(chǔ)。對(duì)于分割得到的運(yùn)動(dòng)片斷,一方面,運(yùn)動(dòng)片斷的長(zhǎng)度越短,對(duì)運(yùn)動(dòng)合成的控制越靈活;另一方面,為了方便用戶(hù)控制,運(yùn)動(dòng)片斷中應(yīng)當(dāng)包含明確的語(yǔ)義信息。我們利用運(yùn)動(dòng)中人體足部的相對(duì)關(guān)系提取運(yùn)動(dòng)特征,在此基礎(chǔ)上,采用運(yùn)動(dòng)捕獲數(shù)據(jù)與運(yùn)動(dòng)模板進(jìn)行匹配的方式,實(shí)現(xiàn)了運(yùn)動(dòng)捕獲數(shù)據(jù)的自動(dòng)分割,避免了繁瑣的手工操作,提高了運(yùn)動(dòng)捕獲數(shù)據(jù)的分割效率和精度;同時(shí),該方法具有很強(qiáng)的魯棒性,運(yùn)動(dòng)分割的正確率比目前廣泛使用的分割方法[KS05]提高了34.12%。 二、在運(yùn)動(dòng)圖的構(gòu)建階段,提出了一種基于參數(shù)化運(yùn)動(dòng)合成的運(yùn)動(dòng)圖方法。 運(yùn)動(dòng)圖方法是一種有效地組織運(yùn)動(dòng)數(shù)據(jù)的方法,運(yùn)動(dòng)圖的本質(zhì)是一種由結(jié)點(diǎn)和邊組成的有向圖。目前運(yùn)動(dòng)圖方法中存儲(chǔ)的僅僅是少數(shù)運(yùn)動(dòng)捕獲數(shù)據(jù),這種方法使得運(yùn)動(dòng)圖的表示能力有限,用戶(hù)的控制精度不高。為此,我們提出了基于參數(shù)化運(yùn)動(dòng)合成的運(yùn)動(dòng)圖方法,該方法的特點(diǎn)在于:其“結(jié)點(diǎn)”對(duì)應(yīng)的是一個(gè)連續(xù)控制參數(shù)空間,給定一組控制參數(shù),如運(yùn)動(dòng)速度、運(yùn)動(dòng)轉(zhuǎn)角等,即可精確地合成出對(duì)應(yīng)的運(yùn)動(dòng)片斷,從而有效地提高了運(yùn)動(dòng)圖的表示能力和用戶(hù)的控制精度;其“邊”表示了不同參數(shù)空間之間的轉(zhuǎn)換關(guān)系,通過(guò)運(yùn)動(dòng)融合實(shí)現(xiàn)了運(yùn)動(dòng)片斷的平滑過(guò)渡,同時(shí),提出了一種根據(jù)約束計(jì)算根關(guān)節(jié)位置的方法,有效的避免了傳統(tǒng)融合方法中腳步滑動(dòng)和根關(guān)節(jié)朝向抖動(dòng)的產(chǎn)生,提高了運(yùn)動(dòng)的逼真性。 三、面向運(yùn)動(dòng)圖的具體應(yīng)用,提出了一種基于路徑的參數(shù)提取方法。 在上述構(gòu)建的運(yùn)動(dòng)圖中,控制參數(shù)是運(yùn)動(dòng)速度、運(yùn)動(dòng)轉(zhuǎn)角等具有明確物理含義的參數(shù)值。然而,用戶(hù)往往需要用直觀的方式控制虛擬人運(yùn)動(dòng),只給定運(yùn)動(dòng)軌跡,即要求能實(shí)時(shí)合成出一段滿(mǎn)足軌跡要求的連續(xù)的運(yùn)動(dòng)序列。為了提供給用戶(hù)一種靈活的交互方式,需要從直觀的路徑軌跡中提取出運(yùn)動(dòng)速度、運(yùn)動(dòng)轉(zhuǎn)角等具體的運(yùn)動(dòng)參數(shù)。本文提出的基于路徑的參數(shù)提取方法,既滿(mǎn)足了運(yùn)動(dòng)合成中實(shí)時(shí)性的要求,又將路徑軌跡和運(yùn)動(dòng)數(shù)據(jù)的屬性緊密結(jié)合起來(lái),使得合成的運(yùn)動(dòng)符合路徑軌跡的要求。試驗(yàn)結(jié)果表明,該方法能夠按照用戶(hù)的軌跡要求實(shí)時(shí)地合成運(yùn)動(dòng)序列。
[Abstract]:Virtual human motion synthesis technology has always been one of the difficulties and hot spots in the field of virtual reality. It is also one of the core technologies of digital culture industry. Security preview and many other fields have broad application prospects. These applications require not only realistic motion effects, but also flexible control of virtual human motion. In this paper, the motion synthesis method based on motion graph is studied in order to meet the needs of these applications, including the preparation of motion graph data, the construction of motion graph and the application of motion graph. The main research results are as follows: firstly, a feature-based automatic segmentation method for human motion capture data is proposed in the data preparation stage of motion map. The reasonable segmentation of motion capture data is the premise and foundation of constructing motion graph. For the segmented motion segment, on the one hand, the shorter the length of the motion segment, the more flexible the control of motion synthesis; on the other hand, in order to facilitate user control, the motion segment should contain explicit semantic information. We use the relative relation of human feet in motion to extract motion features. On this basis, we use the matching method of motion capture data and motion template to realize the automatic segmentation of motion capture data and avoid the tedious manual operation. The efficiency and accuracy of motion acquisition data segmentation are improved, and the method has strong robustness, and the accuracy of motion segmentation is 34.1212% higher than that of the widely used segmentation method [KS05]. Secondly, a motion graph method based on parameterized motion synthesis is proposed in the construction stage of motion graph. Motion graph method is an effective method to organize motion data. The essence of motion graph is a directed graph composed of nodes and edges. At present, only a few motion capture data are stored in the motion graph method, which makes the representation of the motion graph limited and the user's control accuracy is not high. For this reason, we propose a motion graph method based on parameterized motion synthesis. The characteristic of this method is that its "node" corresponds to a continuous control parameter space, and a set of control parameters are given, such as motion velocity, motion rotation angle, etc. The corresponding motion segment can be synthesized accurately, which can effectively improve the expression ability of motion graph and the control accuracy of user, and its "edge" represents the conversion relationship between different parameter spaces. The smooth transition of motion segments is realized by motion fusion. At the same time, a method to calculate the position of root joints according to constraints is proposed, which effectively avoids the occurrence of step sliding and root joint orientation jitter in traditional fusion methods. The motion is more realistic. Thirdly, a path-based parameter extraction method is proposed for the application of motion graph. In the above motion diagram, the control parameters are the values of the motion velocity, the angle of motion and so on, which have definite physical meaning. However, users often need to control the motion of virtual human in an intuitive way. Only a given trajectory is given, that is, a continuous sequence of motion can be synthesized in real time to meet the requirements of trajectory. In order to provide users with a flexible way of interaction, it is necessary to extract the specific motion parameters, such as velocity and angle of motion, from the intuitionistic path. The path-based parameter extraction method proposed in this paper not only meets the real-time requirements of motion synthesis, but also closely combines the path and the attributes of motion data, making the synthesized motion meet the requirements of path trajectory. The experimental results show that the proposed method can synthesize motion sequences in real time according to the user's trajectory requirements.
【學(xué)位授予單位】：首都師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2008
【分類(lèi)號(hào)】：TP391.41
本文編號(hào)：2212057
[Abstract]:Virtual human motion synthesis technology has always been one of the difficulties and hot spots in the field of virtual reality. It is also one of the core technologies of digital culture industry. Security preview and many other fields have broad application prospects. These applications require not only realistic motion effects, but also flexible control of virtual human motion. In this paper, the motion synthesis method based on motion graph is studied in order to meet the needs of these applications, including the preparation of motion graph data, the construction of motion graph and the application of motion graph. The main research results are as follows: firstly, a feature-based automatic segmentation method for human motion capture data is proposed in the data preparation stage of motion map. The reasonable segmentation of motion capture data is the premise and foundation of constructing motion graph. For the segmented motion segment, on the one hand, the shorter the length of the motion segment, the more flexible the control of motion synthesis; on the other hand, in order to facilitate user control, the motion segment should contain explicit semantic information. We use the relative relation of human feet in motion to extract motion features. On this basis, we use the matching method of motion capture data and motion template to realize the automatic segmentation of motion capture data and avoid the tedious manual operation. The efficiency and accuracy of motion acquisition data segmentation are improved, and the method has strong robustness, and the accuracy of motion segmentation is 34.1212% higher than that of the widely used segmentation method [KS05]. Secondly, a motion graph method based on parameterized motion synthesis is proposed in the construction stage of motion graph. Motion graph method is an effective method to organize motion data. The essence of motion graph is a directed graph composed of nodes and edges. At present, only a few motion capture data are stored in the motion graph method, which makes the representation of the motion graph limited and the user's control accuracy is not high. For this reason, we propose a motion graph method based on parameterized motion synthesis. The characteristic of this method is that its "node" corresponds to a continuous control parameter space, and a set of control parameters are given, such as motion velocity, motion rotation angle, etc. The corresponding motion segment can be synthesized accurately, which can effectively improve the expression ability of motion graph and the control accuracy of user, and its "edge" represents the conversion relationship between different parameter spaces. The smooth transition of motion segments is realized by motion fusion. At the same time, a method to calculate the position of root joints according to constraints is proposed, which effectively avoids the occurrence of step sliding and root joint orientation jitter in traditional fusion methods. The motion is more realistic. Thirdly, a path-based parameter extraction method is proposed for the application of motion graph. In the above motion diagram, the control parameters are the values of the motion velocity, the angle of motion and so on, which have definite physical meaning. However, users often need to control the motion of virtual human in an intuitive way. Only a given trajectory is given, that is, a continuous sequence of motion can be synthesized in real time to meet the requirements of trajectory. In order to provide users with a flexible way of interaction, it is necessary to extract the specific motion parameters, such as velocity and angle of motion, from the intuitionistic path. The path-based parameter extraction method proposed in this paper not only meets the real-time requirements of motion synthesis, but also closely combines the path and the attributes of motion data, making the synthesized motion meet the requirements of path trajectory. The experimental results show that the proposed method can synthesize motion sequences in real time according to the user's trajectory requirements.
【學(xué)位授予單位】：首都師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2008
【分類(lèi)號(hào)】：TP391.41
【引證文獻(xiàn)】
相關(guān)碩士學(xué)位論文 前2條
1 郭彬;基于運(yùn)動(dòng)捕獲的角色運(yùn)動(dòng)合成研究與實(shí)現(xiàn)[D];電子科技大學(xué);2010年
2 張?zhí)m蘭;復(fù)雜虛擬場(chǎng)景的語(yǔ)義環(huán)境模型構(gòu)建和人體動(dòng)畫(huà)生成[D];東北石油大學(xué);2012年
，本文編號(hào)：2212057
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