本文選題：運(yùn)動(dòng)捕捉　切入點(diǎn)：攝像機(jī)標(biāo)定　出處：《天津大學(xué)》2009年博士論文

【摘要】： 隨著數(shù)字媒體技術(shù)的迅速發(fā)展,游戲、電影、動(dòng)漫等產(chǎn)業(yè)對(duì)運(yùn)動(dòng)捕捉技術(shù)的需求增長(zhǎng)很快,但是目前購(gòu)買(mǎi)商業(yè)運(yùn)動(dòng)捕捉系統(tǒng)的成本非常高,使用環(huán)境要求嚴(yán)格,需要在演員身上安裝標(biāo)記點(diǎn)等特殊設(shè)備,非常不便。本文結(jié)合計(jì)算機(jī)視覺(jué)和圖形學(xué)相關(guān)技術(shù),提出一套新穎、實(shí)用、成本很低的三維人體模型重建和運(yùn)動(dòng)跟蹤的方法。 首先提出可以同時(shí)進(jìn)行三維特征點(diǎn)重建和攝像機(jī)標(biāo)定的迭代算法。該方法只需要少量的人工交互,算法收斂后可以得到精確的攝像機(jī)參數(shù)和重建模型上的三維特征點(diǎn)。 其次,基于重建的三維特征點(diǎn),使用徑向基函數(shù)對(duì)通用模型進(jìn)行變形,獲得重建的中間模型。實(shí)驗(yàn)表明此方法可以適用于不同體型的對(duì)象,重建模型的質(zhì)量較好,但是由于重建的特征點(diǎn)過(guò)于稀疏,人體的四肢對(duì)應(yīng)不夠好,所以模型還需要進(jìn)一步改進(jìn)。 第三,為了提高重建模型的質(zhì)量,提出以剪影匹配算法為基礎(chǔ)的模型變形算法。該方法較準(zhǔn)確的找到模型剪影和圖像剪影之間的匹配點(diǎn)之后,使用徑向基函數(shù)對(duì)中間模型進(jìn)行變形,提高中間模型投影與圖像的吻合程度,從而獲得目標(biāo)模型。實(shí)驗(yàn)結(jié)果表明目標(biāo)模型在圖像上的平均投影誤差不超過(guò)1個(gè)像素。 第四,為了解決因?yàn)閳D像解析度不夠高和攝像機(jī)標(biāo)定誤差導(dǎo)致的局部走樣問(wèn)題,設(shè)計(jì)了三種過(guò)濾器:平滑過(guò)濾器、切片過(guò)濾器和法線過(guò)濾器,有效的解決了目標(biāo)模型上的鼓包、扭曲變形等需要優(yōu)化的問(wèn)題。 第五,基于圖像的紋理映射通常因?yàn)楣庹詹顒e較大出現(xiàn)紋理不連續(xù)問(wèn)題。本文提出使用旋轉(zhuǎn)切平面將模型切割,然后生成合成紋理的方法。該紋理映射到目標(biāo)模型表面后,效果較好,克服了大部分紋理不連續(xù)的問(wèn)題。 最后,本文提出一種基于分析-合成的三維人體運(yùn)動(dòng)捕捉方法,實(shí)現(xiàn)了無(wú)標(biāo)記點(diǎn)的基于復(fù)雜背景視頻的人體運(yùn)動(dòng)捕捉。該方法對(duì)模型渲染圖像和真實(shí)圖像進(jìn)行匹配,應(yīng)用下山單純形-模擬退火方法最小化匹配誤差。實(shí)驗(yàn)結(jié)果表明此方法可以較準(zhǔn)確穩(wěn)定的進(jìn)行運(yùn)動(dòng)捕捉。
[Abstract]:With the rapid development of digital media technology, the demand for motion capture technology in games, movies, animation and other industries has increased rapidly, but at present the cost of purchasing commercial motion capture systems is very high, and the use of environmental requirements is strict. It is very inconvenient to install special equipment such as marking points on actors. In this paper, a novel, practical and low cost method for 3D human model reconstruction and motion tracking is proposed, which combines computer vision and graphics technology. An iterative algorithm which can reconstruct 3D feature points and calibrate the camera simultaneously is proposed, which requires only a small amount of manual interaction. After the algorithm converges, the exact camera parameters and the 3D feature points on the reconstruction model can be obtained. Secondly, based on the 3D feature points of reconstruction, the general model is deformed by radial basis function (RBF), and the intermediate model is obtained. Experiments show that this method can be applied to objects of different shapes, and the quality of the reconstructed model is good. However, because the feature points of reconstruction are too sparse and the human limbs do not correspond well, the model needs further improvement. Thirdly, in order to improve the quality of the reconstructed model, a model deformation algorithm based on the silhouette matching algorithm is proposed, which finds the matching points between the model silhouette and the image silhouette more accurately. The radial basis function is used to deform the intermediate model to improve the degree of consistency between the projection of the intermediate model and the image. The experimental results show that the average projection error of the target model on the image is less than 1 pixel. Fourthly, in order to solve the problem of local aliasing caused by insufficient image resolution and camera calibration error, three kinds of filters are designed: smooth filter, slice filter and normal filter. Effectively solve the target model on the drum, distortion and other problems that need to be optimized. Fifth, texture discontinuity problem usually occurs in image-based texture mapping because of the large difference in illumination. In this paper, a method of cutting the model by rotating tangent plane and generating synthetic texture is proposed. The texture is mapped to the surface of the target model. The effect is good and the problem of discontinuity of most textures is overcome. Finally, a three-dimensional human motion capture method based on analysis-synthesis is proposed to realize the human motion capture based on complex background video without marking points, which matches the model rendering image with the real image. The method of downhill simplex-simulated annealing is used to minimize the matching error. The experimental results show that this method can be used to capture motion accurately and stably.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2009
【分類(lèi)號(hào)】：TP391.41

【引證文獻(xiàn)】

相關(guān)期刊論文 前1條

1 章成斌;;體育項(xiàng)目運(yùn)動(dòng)學(xué)參數(shù)測(cè)量系統(tǒng)的比較研究[J];武漢體育學(xué)院學(xué)報(bào);2013年01期

，

本文編號(hào)：1664015