基于三维模型的线条画绘制方法研究
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摘要
随着计算机图形学的飞速发展,三维计算机图形已经渗透到计算机应用的方方面面。传统的真实感绘制技术,束缚于忠实的表现场景,无法抛弃琐屑、提取精华,从而不能有效的传达场景的特征信息。非真实感绘制(Non-Photorealistic Rendering,NPR)是近些年来快速发展的一种绘制技术,它主要采用某种艺术风格对物体进行绘制。利用特定的艺术效果对场景信息进行不同层面的抽象,通过这种信息抽象能够清晰明了地表达出场景和物体的特征。这种绘制技术提供了一种有效表达场景信息的途径,弥补真实感绘制方法的局限。线条画绘制是非真实感绘制中很重要的内容,也是其它艺术风格绘制的基础。线条画绘制不仅能通过寥寥几笔勾勒物体形状,还具有丰富的表现力、艺术特质,表达一定的情绪和情感,被广泛应用于美术创作、科技文献插图、动漫游戏、工艺美术及平面广告设计。目前对线条画的研究从数据源上来分主要包括基于三维模型的绘制和基于图像的绘制。而随着游戏动画等数字媒体产业的飞速发展和三维建模技术的不断提高,基于三维空间的非真实感绘制技术变得越来越重要。Range Images是三维模型中很重要的来源,可以很方便地由三维距离扫描仪得到,但这些模型大都粗糙,富含噪声甚至结构残缺,利用目前的算法无法给出令人满意的结果,这样大大制约了这一类模型的应用范围。
为此,本文针对Range Images为代表的三维粗糙模型,融合艺术和认知心理学知识,对非真实感线条画绘制过程中的特征线条检测、特征线条变形和风格化绘制等一系列问题展开研究,为卡通动画等数字娱乐行业提供艺术风格化创作的理论和技术支持。
本文的主要贡献和创新点:
1.提出了一种基于Range Images的特征线条提取算法
针对粗糙、富含噪声甚至结构残缺的模型,提出了一种从Range Images提取特征线条的新算法,同时通过连接和平滑等操作获得适合于进一步风格化渲染的特征线路径,根据这些线条可以生成各种风格的线条画。艺术作品中的特征轮廓线一般是很多轮廓边连接而成,很少有单一的轮廓边孤立存在,该方法利用这一特征,从初始的特征线出发,检测与之连贯的特征轮廓线,从而避免出现大量由模型噪声引发的细小毛刺线条,得到较好的结果。这一思想也可以拓展应用到现有的各类特征线条的提取上,大大降低噪声等因素对特征线条检测造成的影响。
2.提出了一种基于几何属性和领域知识的混合特征提取算法
大多数情况下,基于几何模型的线条提取往往残缺不全,而一味追求基于几何属性的特征线条提取将会大大降低算法的性能和应用范围,结合肖像画绘制的领域知识,通过扩展的线条检测算法从Range Images中检测得到几何线条,从图像纹理中获取特征信息(如肖像画中眼睛、眉毛等区域特征),然后互补融合来自几何模型的特征线条和纹理图像的特征,通过风格化操作完成最后的绘制,从而弥补当前单纯从几何模型或图像出发的处理导致的信息不足,得到细节丰富的肖像画绘制效果。
3.基于特征的线条变形算法
艺术线条的表现力不仅在于忠实物体本身,还体现在对特征的强调和突出。借鉴Focus+Context技术,结合卡通线条画的特征,本文提出了基于特征的线条变形算法,透过变形镜头对该区域中的特征线条变形来实现强调和突出的效果。这种无需样本就可以对三维模型进行所见即所得的实时变形操作可应用在数字娱乐、卡通线条画等动画制作中,通过对变形镜头属性配置和简单的交互操作就可以产生各种富有表现力的效果,实验结果也验证了该方法的可用性和有效性。
4.实现了面向数字娱乐领域的三维肖像画绘制方法
与先前的大多数基于人脸正面照片,或利用模板,或利用五官组成关系,或利用样本学习的办法不同,本系统利用Range Images来实时生成具有中等复杂度的三维艺术肖像画,可应用在各种需要实时交互的应用领域。针对Range Image人脸数据在眼睛眉毛等区域数据采集残缺等特点,采用由RangeImage和标定过的对应纹理图像互补融合生成人脸肖像画的办法,并且进一步通过与平均人脸的比较,对个体人脸进行特征夸张,以凸显其特点,并允许用户通过简单方便的方式进行交互控制,最后经过平滑优化等绘制得到具有特色的人脸肖像。
5.提出移动设备上三维模型的线条画绘制框架
针对移动设备自身存在的屏幕尺寸、分辨率、内存、计算能力、I/O设施等方面的制约,提出并实现了一种通过传输三维模型轮廓特征线条集并在客户端本地绘制的方法,平衡了网络、服务器及客户端的负担,并利用风格化要素来实现生动有趣的非真实感线条画绘制,取得真实感绘制无法比拟的效果。本框架应用在考古数字博物馆的文物展示方面获得了良好的效果,不但增强了参观的体验,还丰富了数字博物馆访问的方式,增强了趣味性和吸引力,使不同层次的公众可以随时随地访博物馆资源。
课题研究成果可以广泛应用于建筑、工业、医学等领域插图生成和数字娱乐行业的游戏动画制作中。在上述研究工作的基础上,下一步还需要更多结合认知心理学和领域知识来对模型信息进行结构化和抽象化,研究线条画风格化理论模型等方面进一步开展工作。
With the rapid development of computer graphics, three-dimensional computer graphics have infiltrated into every aspect of computer applications. Traditional photorealistic rendering purses the gole of realism and is usually restrained from the faithful performance of scenes and can not abandon the irrelevant details, thus can not effectively convey the characteristics of scenes. Non-photorealistic rendering (NPR) in recent years has developped rapidly, which mainly uses some sort of artistic styles to draw target objects. This NPR can show the characteristics of the objects clearly and efficiently by abstracting the target scene at different levels according to the communication expectation or mimicking a specific artistic effect on the scene. This rendering provides an effective way of expressing the scene information to make up for the limitations of photorealistic rendering methods. Line drawings, including sketches, illustrations, and comics, not only take an important part in the NPR domain, but also act as the ingrediant of other artistic styles. Line Drawing is not only able to draw a few strokes to outline the shape of models, but also has a wealth of expressiveness, artistic essential of certain emotions and feelings. Therefore, it is widely used in the areas of art creation, scientific and technical illustrations, 3D games, product design and other related domains. According to the input data type, the current research about line drawings can be devided into three-dimensional space-based rendering and image-based rendering method. The latter-the three-dimensional space of non-photorealistic rendering technique-is becoming increasingly important with the rapid development of digital media industry, such as game animation, and three-dimensional modeling techniques. Range Images, easily attained from range scanner, are very important and common sources of three-dimensional models; but most of these models are rough, noise-rich, or evern structure incompleted. Current algorithms in NPR area can not give satisfactory results on Range Images models and thus constrains the scope of Range Images-related applications.
With the integration of the knowledge of art and cognitive psychology, this thesis gives a series of deep research on NPR line drawings domain, to be more specific, they are research of feature line detection algorithms based on rough, noise-rich models, typically like Range Images, research of feature line deformation, and reseach of stylistic rendering. The research aims to provide the theory and technical support for artistic and efficient rendering in the cartoon animation and other digital entertainment industry.
The main contributions and creative work of this dissertation are as follows:
1. Propose a novel algorithm to extract features lines from Range Images.In order to efficiently extract features from Range Images, usually with the characteristic of rough, noise-rich or even structrure incompleted, we propose an extended feature line extraction algorithm, and further chain and smooth the discreted lines into long line path which is much suitable for the following stylistic process. The main idea of this extended feature lines extraction comes from the artistic observation: most of feature lines in artistic work are not isolated, but connected with each other. Therefore, the algorithm first set a small number of reliable feature lines as the initial reliable starting lines, and then detect those feature lines in consistent with the existing feature lines as far as they satisfy the loose definition of feature lines. Therefore, this method overtakes any other previous algorithms in avoiding a large number of burr lines mainly caused by noise. This idea can also be easily applied to existing types of feature line algorithms, and thus greatly reduce the noise impact on the models.
2. Propose a hybrid method based on the geometry property of 3D models and corresponding instensity images.
In most cases, featue lines from 3D models seem too few to delineate the ensential of the objects. In the domain of human faces, 3D Range Image data and 2D intensity image data are complementary, when producing caricature portraits. Combining geometry lines and texture areas gives a better basis for NPR portrait drawing than a Range Image or intensity image alone could. Using a Range Image as a basis allows viewpoint dependent lines to be drawn, in a way which could not be done from an intensity image. Using a 2D intensity image allows non-geometric information, or information whose geometric boundaries are hard to determine (take the eyes, eyebrows areas in portrait as examples), to be added to the result. Clearly such an approach is applicable to other kinds of drawings than portraits.
3. Propose deformation methods awared of feature lines
The attractiveness of artistic line drawings is not only lies in its ability to fainthfully delineate the object shape, but also lies in the flexible ability of emphasis and highlight on the characteristic of target objects. Inspired by the technology of Focus+Context, the thesis proposes a feature lines deformation method which can exaggereate the most distinctive characteristic features in realtime. When intergrated with the rules from traditional cartoon drawings, the deformation enbables realtime feature exaggeration without sample training but just by simply NPR lens configuration and freely interaction. The expressive experiment result suggests that the methods can be widely used in the area of digital entertainment.
4. Propose a real-time 3D portrait rendering method
The thesis gives a method for automatically creating a caricature drawing-an exaggerated portrait-of a human face, based on simultaneous use of a Range Image (or 3D mesh) and registered photograph of the same face. While previous papers have considered producing portraits from either source individually, we are unaware of methods which combine information from these sources. Unlike most previous template-based, component-based or example-based face sketching methods, which work from a frontal photograph as input; our system uses a Range Image as input. Our method runs in real-time for models of moderate complexity, allowing the pose and drawing style to be modified interactively. We also suggest an approach to facial feature exaggeration for caricaturing a face, based on modifying it relative to an average face. While such variations from the average have been suggested before, we use a different approach to combining the exaggeration applied to different facial features.
5. Propose a framework for the remote rendering of 3D models on mobile devices
Mobile devices, like the Personal Digital Assistant (PDA) and smart phone, enjoy a significant growing number of users up to date. These devices have the limitations on network bandwidth, graphical resources and computing power. To overcome the disadvantages of the devices and balance the workload and performance between the client and server, we present a real time remote rendering method by transferring only the line primitives to client devices from server side, which will be rendered in the client side locally with various non-photorealistic rendering techniques. When applied into the digital museum exhibition, it allows the user to interactively go through the 3D models with his personal mobile device anytime and anywhere. Moreover, we can enrich the users' experience since NPR based images are usually eyes attracting.
This research shares applications with those of traditional hand-generated techniques, including architectural and product design, technical and medical illustration, storytelling (e.g. children' s books), games, fine arts, and animation. Indeed we have solved some key and fundamental problem to some degree when dealing with lines drawing of three models on Range Images models. However, there are some aspects needed further improvements. We in the future should take more consideration of cognitive psychology and domain knowledge in order to better understanding the target object when abstraction and strulization. Moreover, we might further focus on constructing the general stylitic theory model which fundumently would push the prosperity of NPR era.
为此,本文针对Range Images为代表的三维粗糙模型,融合艺术和认知心理学知识,对非真实感线条画绘制过程中的特征线条检测、特征线条变形和风格化绘制等一系列问题展开研究,为卡通动画等数字娱乐行业提供艺术风格化创作的理论和技术支持。
本文的主要贡献和创新点:
1.提出了一种基于Range Images的特征线条提取算法
针对粗糙、富含噪声甚至结构残缺的模型,提出了一种从Range Images提取特征线条的新算法,同时通过连接和平滑等操作获得适合于进一步风格化渲染的特征线路径,根据这些线条可以生成各种风格的线条画。艺术作品中的特征轮廓线一般是很多轮廓边连接而成,很少有单一的轮廓边孤立存在,该方法利用这一特征,从初始的特征线出发,检测与之连贯的特征轮廓线,从而避免出现大量由模型噪声引发的细小毛刺线条,得到较好的结果。这一思想也可以拓展应用到现有的各类特征线条的提取上,大大降低噪声等因素对特征线条检测造成的影响。
2.提出了一种基于几何属性和领域知识的混合特征提取算法
大多数情况下,基于几何模型的线条提取往往残缺不全,而一味追求基于几何属性的特征线条提取将会大大降低算法的性能和应用范围,结合肖像画绘制的领域知识,通过扩展的线条检测算法从Range Images中检测得到几何线条,从图像纹理中获取特征信息(如肖像画中眼睛、眉毛等区域特征),然后互补融合来自几何模型的特征线条和纹理图像的特征,通过风格化操作完成最后的绘制,从而弥补当前单纯从几何模型或图像出发的处理导致的信息不足,得到细节丰富的肖像画绘制效果。
3.基于特征的线条变形算法
艺术线条的表现力不仅在于忠实物体本身,还体现在对特征的强调和突出。借鉴Focus+Context技术,结合卡通线条画的特征,本文提出了基于特征的线条变形算法,透过变形镜头对该区域中的特征线条变形来实现强调和突出的效果。这种无需样本就可以对三维模型进行所见即所得的实时变形操作可应用在数字娱乐、卡通线条画等动画制作中,通过对变形镜头属性配置和简单的交互操作就可以产生各种富有表现力的效果,实验结果也验证了该方法的可用性和有效性。
4.实现了面向数字娱乐领域的三维肖像画绘制方法
与先前的大多数基于人脸正面照片,或利用模板,或利用五官组成关系,或利用样本学习的办法不同,本系统利用Range Images来实时生成具有中等复杂度的三维艺术肖像画,可应用在各种需要实时交互的应用领域。针对Range Image人脸数据在眼睛眉毛等区域数据采集残缺等特点,采用由RangeImage和标定过的对应纹理图像互补融合生成人脸肖像画的办法,并且进一步通过与平均人脸的比较,对个体人脸进行特征夸张,以凸显其特点,并允许用户通过简单方便的方式进行交互控制,最后经过平滑优化等绘制得到具有特色的人脸肖像。
5.提出移动设备上三维模型的线条画绘制框架
针对移动设备自身存在的屏幕尺寸、分辨率、内存、计算能力、I/O设施等方面的制约,提出并实现了一种通过传输三维模型轮廓特征线条集并在客户端本地绘制的方法,平衡了网络、服务器及客户端的负担,并利用风格化要素来实现生动有趣的非真实感线条画绘制,取得真实感绘制无法比拟的效果。本框架应用在考古数字博物馆的文物展示方面获得了良好的效果,不但增强了参观的体验,还丰富了数字博物馆访问的方式,增强了趣味性和吸引力,使不同层次的公众可以随时随地访博物馆资源。
课题研究成果可以广泛应用于建筑、工业、医学等领域插图生成和数字娱乐行业的游戏动画制作中。在上述研究工作的基础上,下一步还需要更多结合认知心理学和领域知识来对模型信息进行结构化和抽象化,研究线条画风格化理论模型等方面进一步开展工作。
With the rapid development of computer graphics, three-dimensional computer graphics have infiltrated into every aspect of computer applications. Traditional photorealistic rendering purses the gole of realism and is usually restrained from the faithful performance of scenes and can not abandon the irrelevant details, thus can not effectively convey the characteristics of scenes. Non-photorealistic rendering (NPR) in recent years has developped rapidly, which mainly uses some sort of artistic styles to draw target objects. This NPR can show the characteristics of the objects clearly and efficiently by abstracting the target scene at different levels according to the communication expectation or mimicking a specific artistic effect on the scene. This rendering provides an effective way of expressing the scene information to make up for the limitations of photorealistic rendering methods. Line drawings, including sketches, illustrations, and comics, not only take an important part in the NPR domain, but also act as the ingrediant of other artistic styles. Line Drawing is not only able to draw a few strokes to outline the shape of models, but also has a wealth of expressiveness, artistic essential of certain emotions and feelings. Therefore, it is widely used in the areas of art creation, scientific and technical illustrations, 3D games, product design and other related domains. According to the input data type, the current research about line drawings can be devided into three-dimensional space-based rendering and image-based rendering method. The latter-the three-dimensional space of non-photorealistic rendering technique-is becoming increasingly important with the rapid development of digital media industry, such as game animation, and three-dimensional modeling techniques. Range Images, easily attained from range scanner, are very important and common sources of three-dimensional models; but most of these models are rough, noise-rich, or evern structure incompleted. Current algorithms in NPR area can not give satisfactory results on Range Images models and thus constrains the scope of Range Images-related applications.
With the integration of the knowledge of art and cognitive psychology, this thesis gives a series of deep research on NPR line drawings domain, to be more specific, they are research of feature line detection algorithms based on rough, noise-rich models, typically like Range Images, research of feature line deformation, and reseach of stylistic rendering. The research aims to provide the theory and technical support for artistic and efficient rendering in the cartoon animation and other digital entertainment industry.
The main contributions and creative work of this dissertation are as follows:
1. Propose a novel algorithm to extract features lines from Range Images.In order to efficiently extract features from Range Images, usually with the characteristic of rough, noise-rich or even structrure incompleted, we propose an extended feature line extraction algorithm, and further chain and smooth the discreted lines into long line path which is much suitable for the following stylistic process. The main idea of this extended feature lines extraction comes from the artistic observation: most of feature lines in artistic work are not isolated, but connected with each other. Therefore, the algorithm first set a small number of reliable feature lines as the initial reliable starting lines, and then detect those feature lines in consistent with the existing feature lines as far as they satisfy the loose definition of feature lines. Therefore, this method overtakes any other previous algorithms in avoiding a large number of burr lines mainly caused by noise. This idea can also be easily applied to existing types of feature line algorithms, and thus greatly reduce the noise impact on the models.
2. Propose a hybrid method based on the geometry property of 3D models and corresponding instensity images.
In most cases, featue lines from 3D models seem too few to delineate the ensential of the objects. In the domain of human faces, 3D Range Image data and 2D intensity image data are complementary, when producing caricature portraits. Combining geometry lines and texture areas gives a better basis for NPR portrait drawing than a Range Image or intensity image alone could. Using a Range Image as a basis allows viewpoint dependent lines to be drawn, in a way which could not be done from an intensity image. Using a 2D intensity image allows non-geometric information, or information whose geometric boundaries are hard to determine (take the eyes, eyebrows areas in portrait as examples), to be added to the result. Clearly such an approach is applicable to other kinds of drawings than portraits.
3. Propose deformation methods awared of feature lines
The attractiveness of artistic line drawings is not only lies in its ability to fainthfully delineate the object shape, but also lies in the flexible ability of emphasis and highlight on the characteristic of target objects. Inspired by the technology of Focus+Context, the thesis proposes a feature lines deformation method which can exaggereate the most distinctive characteristic features in realtime. When intergrated with the rules from traditional cartoon drawings, the deformation enbables realtime feature exaggeration without sample training but just by simply NPR lens configuration and freely interaction. The expressive experiment result suggests that the methods can be widely used in the area of digital entertainment.
4. Propose a real-time 3D portrait rendering method
The thesis gives a method for automatically creating a caricature drawing-an exaggerated portrait-of a human face, based on simultaneous use of a Range Image (or 3D mesh) and registered photograph of the same face. While previous papers have considered producing portraits from either source individually, we are unaware of methods which combine information from these sources. Unlike most previous template-based, component-based or example-based face sketching methods, which work from a frontal photograph as input; our system uses a Range Image as input. Our method runs in real-time for models of moderate complexity, allowing the pose and drawing style to be modified interactively. We also suggest an approach to facial feature exaggeration for caricaturing a face, based on modifying it relative to an average face. While such variations from the average have been suggested before, we use a different approach to combining the exaggeration applied to different facial features.
5. Propose a framework for the remote rendering of 3D models on mobile devices
Mobile devices, like the Personal Digital Assistant (PDA) and smart phone, enjoy a significant growing number of users up to date. These devices have the limitations on network bandwidth, graphical resources and computing power. To overcome the disadvantages of the devices and balance the workload and performance between the client and server, we present a real time remote rendering method by transferring only the line primitives to client devices from server side, which will be rendered in the client side locally with various non-photorealistic rendering techniques. When applied into the digital museum exhibition, it allows the user to interactively go through the 3D models with his personal mobile device anytime and anywhere. Moreover, we can enrich the users' experience since NPR based images are usually eyes attracting.
This research shares applications with those of traditional hand-generated techniques, including architectural and product design, technical and medical illustration, storytelling (e.g. children' s books), games, fine arts, and animation. Indeed we have solved some key and fundamental problem to some degree when dealing with lines drawing of three models on Range Images models. However, there are some aspects needed further improvements. We in the future should take more consideration of cognitive psychology and domain knowledge in order to better understanding the target object when abstraction and strulization. Moreover, we might further focus on constructing the general stylitic theory model which fundumently would push the prosperity of NPR era.
引文
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42. Gooch, B., Reinhard E., Gooch A. Human facial illustrations: Creation and psychophysical evaluation. ACM Transactions on Graphics, 2004, 23(1):27-44.
43. Chiang P. Y., Liao W. H., Li T.Y. Automatic Caricature Generation by Analyzing Facial Features. Proceeding of 2003 National Computer Symposium, 2003, 89-94.
44. Chen H, Liu Z. Q., Rose C. Example-based composite sketching of human portraits. Proceedings of NPAR'04,2004, 95-153.
45. Xu Z. J., Chen H., Zhu S. C. A Hierarchical Compositional Model for Face Representation and Sketching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(6): 955-969.
46. Liang L., Chen H., Xu Y. Q. Example-based caricature generation with exaggeration. Proceedings of 10th Pacific Conference on Computer Graphic and Application, 2002, 386-393.
47. Roman Z. , Pavel S. Non-Photorealistic Walkthroughs Using Flash. Proceedings of WSCG POSTERS, 2004,201-204.
48. Hekmatzada D., Meseth J., Klein R. Non-Photorealistic Rendering of Complex 3D Models on Mobile Devices. The 8th Annual Conference of the International Association for Mathematical Geology, 2002, 93-98.
49. Sanna A., Zunino C., Lamberti F. A distributed architecture for searching,retrieving and visualizing complex 3D models on Personal Digital Assistants.International Journal of Human-Computer Studies, 2004,60 (5):701-716.
50. Teler E., Lischinski D. Streaming of Complex 3D Scenes for Remote Walkthroughs. Computer Graphics Forum, 2000, 20(3): 17-25.
51. Finkelstein A., Salesin D.H. Multiresolution Curves. SIGGRAPH'94:Proceedings of the 21st annual conference on Computer graphics and interactive techniques, 1994,261-268.
52. Hertzmann A., Oliver N, Curless B., Steven M.. Curve analogies.Proceedings of the 13th Eurographics workshop on Rendering, 2002, 26-28.
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54. Hsu S. C, Lee I. H. H. Drawing and animation using skeletal strokes.SIGGRAPH'94: Proceedings of the 21st annual conference on Computer graphics and interactive techniques, 1994, 109-118.
55.杨刚,孟祥旭、屠长河.利用带约束的图案变形算法生成笔画效果.计算机辅助设计与图形学学报,2003,15(1):65-70.
56.Isenberg T.,Freudenberg B.,Halper N.,Schlechtweg S.,Strothotte T.A Developer's Guide to Silhouette Algorithms for Polygonal Models.IEEE Computer Graphic and Applications,2003,23(4):28-37.
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