CN111583422B - Heuristic editing method and device for three-dimensional human body model - Google Patents
Heuristic editing method and device for three-dimensional human body model Download PDFInfo
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Abstract
Description
技术领域technical field
本发明涉及计算机视觉、计算机图形学技术领域,特别涉及一种三维人体模型的启发式编辑方法及装置。The invention relates to the technical fields of computer vision and computer graphics, in particular to a heuristic editing method and device for a three-dimensional human body model.
背景技术Background technique
三维人体模型的编辑是计算机图形学领域的一个重要问题。但三维人体模型的编辑成本往往很高,传统的三维模型编辑方法步骤繁琐,需要专业的模型动画师完成,并且费时费力。Editing of 3D human body models is an important problem in the field of computer graphics. However, the cost of editing 3D human body models is often very high. The traditional 3D model editing methods are cumbersome, require professional model animators to complete, and are time-consuming and labor-intensive.
近年来,深度神经网络的快速发展为很多“从无到有”的问题提供了一种解决思路。但三维神经网络的成熟度不如二维神经网络,因此,三维问题还无法像二维问题那样用基于神经网络的方法得到解决。In recent years, the rapid development of deep neural networks has provided a solution to many "from scratch" problems. However, the maturity of the 3D neural network is not as good as that of the 2D neural network. Therefore, the 3D problem cannot be solved by the method based on the neural network like the 2D problem.
发明内容Contents of the invention
本发明旨在至少在一定程度上解决相关技术中的技术问题之一。The present invention aims to solve one of the technical problems in the related art at least to a certain extent.
为此,本发明的一个目的在于提出一种三维人体模型的启发式编辑方法,该方法可以大大简化三维人体模型的编辑。Therefore, an object of the present invention is to propose a heuristic editing method for a three-dimensional human body model, which can greatly simplify the editing of the three-dimensional human body model.
本发明的另一个目的在于提出一种三维人体模型的启发式编辑装置。Another object of the present invention is to propose a heuristic editing device for a three-dimensional human body model.
为达到上述目的,本发明一方面实施例提出了三维人体模型的启发式编辑方法,包括以下步骤:步骤S1,获取待编辑的三维人体模型;步骤S2,利用曲面参数化方法将所述待编辑的三维人体模型转换为几何图像;步骤S3,处理所述几何图像对二维神经网络进行训练,输出生成几何图像,并将所述生成几何图像反转化为三维信息。In order to achieve the above purpose, an embodiment of the present invention proposes a heuristic editing method for a three-dimensional human body model, including the following steps: step S1, obtaining the three-dimensional human body model to be edited; step S2, using the surface parameterization method to convert the The three-dimensional human body model is converted into a geometric image; step S3, processing the geometric image to train a two-dimensional neural network, outputting a generated geometric image, and inverting the generated geometric image into three-dimensional information.
本发明实施例的三维人体模型的启发式编辑方法,利用曲面参数化和深度神经网络技术,人为提供启发式的草图,生成带有相应细节的人体模型,大大简化了三维人体模型的编辑。The heuristic editing method of the 3D human body model in the embodiment of the present invention uses surface parameterization and deep neural network technology to artificially provide heuristic sketches to generate a human body model with corresponding details, which greatly simplifies the editing of the 3D human body model.
另外,根据本发明上述实施例的三维人体模型的启发式编辑方法还可以具有以下附加的技术特征:In addition, the heuristic editing method for a three-dimensional human body model according to the above-mentioned embodiments of the present invention may also have the following additional technical features:
进一步地,在本发明的一个实施例中,所述步骤S3包括:通过边缘检测算法提取所述几何图形的线条图像,并随机生成掩码图像;对所述几何图像和所述掩码图像进行掩码计算,得到二维残缺图像;利用所述二维残缺图像对所述二维神经网络进行训练。Further, in one embodiment of the present invention, the step S3 includes: extracting the line image of the geometric figure through an edge detection algorithm, and randomly generating a mask image; performing a process on the geometric image and the mask image The mask is calculated to obtain a two-dimensional incomplete image; the two-dimensional neural network is trained by using the two-dimensional incomplete image.
进一步地,在本发明的一个实施例中,所述步骤S1还获取用户选定的编辑区。Further, in an embodiment of the present invention, the step S1 also obtains the editing area selected by the user.
进一步地,在本发明的一个实施例中,在获得所述几何图像前,需在用户选定的编辑区内选取一条或多条想要变形的顶点链,利用所述顶点链生成线条图像,即编辑草图。Further, in one embodiment of the present invention, before obtaining the geometric image, it is necessary to select one or more vertex chains to be deformed in the editing area selected by the user, and use the vertex chains to generate a line image, i.e. Edit Sketch.
进一步地,在本发明的一个实施例中,根据所述用户选定的编辑区映射出掩码图像。Further, in an embodiment of the present invention, a mask image is mapped out according to the editing area selected by the user.
为达到上述目的,本发明另一方面实施例提出了三维人体模型的启发式编辑装置,包括:获取模块,用于获取待编辑的三维人体模型;转换模块,用于利用曲面参数化方法将所述待编辑的三维人体模型转换为几何图像;训练模块,用于处理所述几何图像对二维神经网络进行训练,输出生成几何图像,并将所述生成几何图像反转化为三维信息。In order to achieve the above object, another embodiment of the present invention proposes a heuristic editing device for a 3D human body model, including: an acquisition module for acquiring a 3D human body model to be edited; a conversion module for converting the 3D human body model to The three-dimensional human body model to be edited is converted into a geometric image; the training module is used to process the geometric image to train the two-dimensional neural network, output the generated geometric image, and reversely convert the generated geometric image into three-dimensional information.
本发明实施例的三维人体模型的启发式编辑装置,利用曲面参数化和深度神经网络技术,人为提供启发式的草图,生成带有相应细节的人体模型,大大简化了三维人体模型的编辑。The heuristic editing device for the 3D human body model in the embodiment of the present invention uses surface parameterization and deep neural network technology to artificially provide heuristic sketches to generate a human body model with corresponding details, which greatly simplifies the editing of the 3D human body model.
另外,根据本发明上述实施例的三维人体模型的启发式编辑装置还可以具有以下附加的技术特征:In addition, the device for heuristic editing of a three-dimensional human body model according to the above-mentioned embodiments of the present invention may also have the following additional technical features:
进一步地,在本发明的一个实施例中,所述训练模块包括:提取单元,用于通过边缘检测算法提取所述几何图形的线条图像,并随机生成掩码图像;计算模块,用于对所述几何图像和所述掩码图像进行掩码计算,得到二维残缺图像;训练单元,用于利用所述二维残缺图像对所述二维神经网络进行训练。Further, in one embodiment of the present invention, the training module includes: an extraction unit, used to extract the line image of the geometric figure through an edge detection algorithm, and randomly generate a mask image; performing mask calculation on the geometric image and the mask image to obtain a two-dimensional incomplete image; a training unit configured to use the two-dimensional incomplete image to train the two-dimensional neural network.
进一步地,在本发明的一个实施例中,所述获取模块还用于获取用户选定的编辑区。Further, in an embodiment of the present invention, the obtaining module is also used to obtain the editing area selected by the user.
进一步地,在本发明的一个实施例中,在获得所述几何图像前,需在用户选定的编辑区内选取一条或多条想要变形的顶点链,利用所述顶点链生成线条图像即编辑草图。Further, in one embodiment of the present invention, before obtaining the geometric image, it is necessary to select one or more vertex chains to be deformed in the editing area selected by the user, and use the vertex chains to generate a line image that is Edit the sketch.
进一步地,在本发明的一个实施例中,根据所述用户选定的编辑区映射出掩码图像。Further, in an embodiment of the present invention, a mask image is mapped out according to the editing area selected by the user.
本发明附加的方面和优点将在下面的描述中部分给出,部分将从下面的描述中变得明显,或通过本发明的实践了解到。Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
附图说明Description of drawings
本发明上述的和/或附加的方面和优点从下面结合附图对实施例的描述中将变得明显和容易理解,其中:The above and/or additional aspects and advantages of the present invention will become apparent and easy to understand from the following description of the embodiments in conjunction with the accompanying drawings, wherein:
图1为根据本发明一个实施例的三维人体模型的启发式编辑方法的流程图;Fig. 1 is a flowchart of a heuristic editing method for a three-dimensional human body model according to an embodiment of the present invention;
图2为根据本发明一个实施例的三维人体模型的启发式编辑装置的结构示意图。Fig. 2 is a schematic structural diagram of a heuristic editing device for a 3D human body model according to an embodiment of the present invention.
具体实施方式Detailed ways
下面详细描述本发明的实施例,实施例的示例在附图中示出,其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的,旨在用于解释本发明,而不能理解为对本发明的限制。Embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.
下面参照附图描述根据本发明实施例提出的三维人体模型的启发式编辑方法及装置,首先将参照附图描述根据本发明实施例提出的三维人体模型的启发式编辑方法。The following describes the heuristic editing method and device for a 3D human body model according to the embodiments of the present invention with reference to the accompanying drawings. First, the heuristic editing method for the 3D human body model according to the embodiments of the present invention will be described with reference to the accompanying drawings.
需要说明的是,所谓启发式编辑方法,指的是编辑者为编辑器提供一种“建议”。编辑器生成的结果不一定与“建议”完全一致,但会朝着“建议”的方向进行相应的修改。即在舍弃一定编辑准确度的情况下,大大简化编辑的流程。It should be noted that the so-called heuristic editing method refers to the editor providing a "suggestion" to the editor. The results generated by the editor may not be exactly the same as the "suggestions", but corresponding modifications will be made in the direction of the "suggestions". That is to say, the editing process is greatly simplified while sacrificing a certain editing accuracy.
图1是本发明一个实施例的三维人体模型的启发式编辑方法的流程图。Fig. 1 is a flowchart of a heuristic editing method for a 3D human body model according to an embodiment of the present invention.
如图1所示,该三维人体模型的启发式编辑方法包括以下步骤:As shown in Figure 1, the heuristic editing method of the 3D human body model includes the following steps:
在步骤S1中,获取待编辑的三维人体模型。In step S1, a three-dimensional human body model to be edited is obtained.
进一步地,步骤S1还获取用户选定的编辑区,其中,本发明实施例可以根据用户输入的草图,对选定的编辑区域的三维几何进行修改。Further, step S1 also acquires the editing area selected by the user, wherein the embodiment of the present invention can modify the three-dimensional geometry of the selected editing area according to the sketch input by the user.
在步骤S2中,利用曲面参数化方法将待编辑的三维人体模型转换为几何图像。In step S2, the three-dimensional human body model to be edited is converted into a geometric image by using a surface parameterization method.
可以理解的是,当前三维神经网络与二维神经网络相比成熟度不高。利用曲面参数化的方法将三维信息转化为易于处理的二维信息,便于神经网络进行处理。可逆的转化方式又使得信息在转化前后不会有过大的丢失。Understandably, current 3D neural networks are less mature than 2D neural networks. The three-dimensional information is converted into easy-to-handle two-dimensional information by means of surface parameterization, which is convenient for neural network processing. The reversible conversion method also prevents the information from being lost too much before and after the conversion.
进一步地,在本发明的一个实施例中,在获得几何图像前,需在用户选定的编辑区内选取一条或多条想要变形的顶点链,利用顶点链生成线条图像。Further, in one embodiment of the present invention, before obtaining the geometric image, one or more vertex chains to be deformed need to be selected in the editing area selected by the user, and a line image is generated by using the vertex chains.
需要说明的是,传统的三维编辑方法往往需要多次选取不同的草图面进行不同视角上的编辑,本发明实施例仅需要通过选取顶点链(由按一定顺序连接的多个顶点组成)的方式自动生成线条图像(即草图),无需定义草图面,摆脱了视角的限制,简化了编辑步骤。It should be noted that traditional 3D editing methods often require multiple selections of different sketch surfaces for editing at different viewing angles. The embodiment of the present invention only needs to select a vertex chain (composed of multiple vertices connected in a certain order) Automatically generate line images (that is, sketches), no need to define sketch faces, get rid of the limitation of viewing angle, and simplify the editing steps.
在步骤S3中,处理几何图像对二维神经网络进行训练,输出生成几何图像,并将生成几何图像转化为三维信息。In step S3, process the geometric image to train the two-dimensional neural network, output the generated geometric image, and convert the generated geometric image into three-dimensional information.
具体地,通过边缘检测算法提取几何图形的线条图像,并随机生成掩码图像;对几何图像和掩码图像进行掩码计算,得到二维残缺图像;利用二维残缺图像对二维神经网络进行训练。向训练好的二维神经网络输入待编辑的三维人体模型,输出生成几何图像,将该二维信息反转化为三维信息。其中,根据用户选定的编辑区随机映射出掩码图像。Specifically, the line image of the geometric figure is extracted through the edge detection algorithm, and a mask image is randomly generated; the mask calculation is performed on the geometric image and the mask image to obtain a two-dimensional incomplete image; train. Input the 3D human body model to be edited into the trained 2D neural network, output the generated geometric image, and convert the 2D information into 3D information. Wherein, the mask image is randomly mapped according to the editing area selected by the user.
需要说明的是,本发明实施例只编码人体模型(含衣物细节)相对于人体模型(裸体)三维坐标的差值。人体模型在xyz三轴上的数值范围差异过大,通过只编码差值的方式可以将数值范围进行统一,保留了更多细节信息,方便神经网络进行训练。It should be noted that the embodiment of the present invention only encodes the difference between the three-dimensional coordinates of the human body model (including clothing details) relative to the human body model (naked). The numerical range of the human body model on the xyz three axes is too different. By only encoding the difference, the numerical range can be unified, and more detailed information is retained, which is convenient for neural network training.
下面结合具体示例对本发明的三维人体模型的启发式编辑方法做进一步描述。The heuristic editing method of the 3D human body model of the present invention will be further described below with reference to specific examples.
该具体示例将三维信息转换为512×512×3的二维图像。3个图像通道分别用于存储xyz维度上的信息。由于涉及到神经网络的训练与使用,以下步骤分为训练步骤以及使用步骤。This specific example converts three-dimensional information into a 512×512×3 two-dimensional image. The three image channels are used to store information in the xyz dimension respectively. Since it involves the training and use of the neural network, the following steps are divided into training steps and usage steps.
训练步骤1:利用曲面参数化的方法将数据集中的人体模型(含衣物细节)相对于人体模型(裸体)的三维坐标差值转换为512×512×3的二维图像(以下简称为“几何图像”)。Training step 1: Use the surface parameterization method to convert the three-dimensional coordinate difference between the human body model (including clothing details) and the human body model (naked) in the data set into a 512×512×3 two-dimensional image (hereinafter referred to as “geometry image").
训练步骤2:利用边缘检测算法提取几何图像的512×512×1线条图像;Training step 2: using edge detection algorithm to extract 512×512×1 line image of geometric image;
训练步骤3:随机生成512×512×1的掩码图像;Training step 3: Randomly generate a mask image of 512×512×1;
训练步骤4:训练一个二维神经网络,其输入为512×512×3的二维残缺图像(由几何图像与掩码图像进行掩码计算得到)和512×512×1的线条图像,其输出为512×512×3的生成几何图像。训练时,除了原几何图像与生成几何图像之间的L1损失约束外,还利用对抗训练技术,通过设置一个判别网络,将原几何图像作为正样本,生成几何图像作为负样本,提高生成结果的多样性。Training step 4: train a two-dimensional neural network, the input of which is a 512×512×3 two-dimensional incomplete image (obtained by the mask calculation of the geometric image and the mask image) and a 512×512×1 line image, and its output Generate geometric images for 512x512x3. During training, in addition to the L1 loss constraint between the original geometric image and the generated geometric image, an adversarial training technique is also used to set up a discriminant network, using the original geometric image as a positive sample and the generated geometric image as a negative sample to improve the accuracy of the generated results. diversity.
使用步骤1:选取需要编辑的三维人体区域;Step 1: Select the 3D human body area to be edited;
使用步骤2:在上述编辑区域内,选取一条或多条想要变形的顶点链(由按一定顺序连接的多个顶点组成);Step 2: In the above editing area, select one or more vertex chains (consisting of multiple vertices connected in a certain order) that you want to deform;
使用步骤3:利用之前定义的曲面参数化映射,本发明实施例会自动地将待编辑人体模型映射为512×512×3的几何图像,自动地将使用步骤1的编辑区域映射成512×512×1掩码图像,自动地将使用步骤2的顶点链映射成512×512×1的线条图像,并将上述信息输入给训练好的神经网络,输出生成几何图像;Using step 3: Using the previously defined surface parameterized mapping, the embodiment of the present invention will automatically map the human body model to be edited into a 512×512×3 geometric image, and automatically map the editing area using step 1 into a 512×512× 1 mask image, automatically map the vertex chain used in step 2 into a 512×512×1 line image, and input the above information to the trained neural network, and output a geometric image;
使用步骤4:本发明实施例会自动地将网络生成的几何图像反转化为三维信息,从而得到生成的三维人体模型。Step 4: the embodiment of the present invention will automatically convert the geometric image generated by the network into three-dimensional information, so as to obtain the generated three-dimensional human body model.
根据本发明实施例提出的三维人体模型的启发式编辑方法,通过曲面参数化的方法将用户输入的三维信息转化为易于处理的二维信息,通过二维深度神经网络处理后,反转化为三维信息呈现出来,简化了繁琐的三维编辑操作,图与视角无关,并无线条数量限制,能够生成衣物的褶皱细节。According to the heuristic editing method of the three-dimensional human body model proposed by the embodiment of the present invention, the three-dimensional information input by the user is converted into easy-to-handle two-dimensional information through the surface parameterization method, and after being processed by the two-dimensional deep neural network, it is reversely transformed into The 3D information is presented, which simplifies the cumbersome 3D editing operations. The graph has nothing to do with the viewing angle, and there is no limit on the number of lines, which can generate the details of the folds of the clothes.
其次参照附图描述根据本发明实施例提出的三维人体模型的启发式编辑装置。Next, a heuristic editing device for a three-dimensional human body model according to an embodiment of the present invention is described with reference to the accompanying drawings.
图2是本发明一个实施例的三维人体模型的启发式编辑装置的结构示意图。Fig. 2 is a schematic structural diagram of a heuristic editing device for a 3D human body model according to an embodiment of the present invention.
如图2所示,该装置10包括:获取模块100、转换模块200和训练模块300。As shown in FIG. 2 , the
其中,获取模块100用于获取待编辑的三维人体模型。转换模块200用于利用曲面参数化方法将待编辑的三维人体模型转换为几何图像,。训练模块300用于处理几何图像对二维神经网络进行训练,输出生成几何图像,并将生成几何图像反转化为三维信息。Wherein, the obtaining
进一步地,在本发明的一个实施例中,训练模块300包括:提取单元,用于通过边缘检测算法提取几何图形的线条图像,并随机生成掩码图像;计算模块,用于对几何图像和掩码图像进行掩码计算,得到二维残缺图像;训练单元,用于利用二维残缺图像对二维神经网络进行训练。Further, in one embodiment of the present invention, the
进一步地,在本发明的一个实施例中,获取模块还用于获取用户选定的编辑区。Further, in an embodiment of the present invention, the obtaining module is also used to obtain the editing area selected by the user.
进一步地,在本发明的一个实施例中,在获得几何图像前,需在用户选定的编辑区内选取一条或多条想要变形的顶点链,利用顶点链生成线条图像(即编辑草图)。Further, in one embodiment of the present invention, before obtaining the geometric image, it is necessary to select one or more vertex chains to be deformed in the editing area selected by the user, and use the vertex chains to generate line images (that is, edit sketches) .
进一步地,在本发明的一个实施例中,根据用户选定的编辑区映射出掩码图像。Further, in an embodiment of the present invention, the mask image is mapped out according to the editing area selected by the user.
根据本发明实施例提出的三维人体模型的启发式编辑装置,通过曲面参数化的方法将用户输入的三维信息转化为易于处理的二维信息,通过二维深度神经网络处理后,反转化为三维信息呈现出来,简化了繁琐的三维编辑操作,图与视角无关,并无线条数量限制,能够生成衣物的褶皱细节。According to the heuristic editing device of the 3D human body model proposed in the embodiment of the present invention, the 3D information input by the user is converted into easy-to-handle 2D information through the surface parameterization method, and after being processed by the 2D deep neural network, it is reversely transformed into The 3D information is presented, which simplifies the cumbersome 3D editing operations. The graph has nothing to do with the viewing angle, and there is no limit on the number of lines, which can generate the details of the folds of the clothes.
此外,术语“第一”、“第二”仅用于描述目的,而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此,限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本发明的描述中,“多个”的含义是至少两个,例如两个,三个等,除非另有明确具体的限定。In addition, the terms "first" and "second" are used for descriptive purposes only, and cannot be interpreted as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of these features. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.
在本说明书的描述中,参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中,对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且,描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外,在不相互矛盾的情况下,本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。In the description of this specification, descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific examples", or "some examples" mean that specific features described in connection with the embodiment or example , structure, material or characteristic is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the described specific features, structures, materials or characteristics may be combined in any suitable manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples and features of different embodiments or examples described in this specification without conflicting with each other.
尽管上面已经示出和描述了本发明的实施例,可以理解的是,上述实施例是示例性的,不能理解为对本发明的限制,本领域的普通技术人员在本发明的范围内可以对上述实施例进行变化、修改、替换和变型。Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention, those skilled in the art can make the above-mentioned The embodiments are subject to changes, modifications, substitutions and variations.
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