基于时空关系的在线多笔划手绘直线段识别

综合考虑笔划的时空关系对在线多笔划手绘直线段进行识别。基于时间关系进行多笔划预处理;详细讨论基于空间关系的多笔划绘制直线段的识别方法。提出利用两条笔划拟合直线段间的位置关系进行多笔划判定的方法;提出依据其原有拟合特征的多笔划直线段拟合方法及相应的首尾点确定方法;并给出带线型直线段的完整定义。通过算例对提出的算法加以验证和应用。     

基于时空关系的在线多笔画手绘折线段曲线识别

基于在线笔画的时空关系对多笔画手绘折线段曲线进行识别,先基于时间间断对笔画序列进行多笔画预处理,然后详细讨论基于空间关系的多笔画手绘折线段的识别问题。将折线段的多笔画识别分为折线段与直线段的多笔画识别和折线段间的多笔画识别。在讨论折线段与折线段间的多笔画绘制时,给出点与折线段及两条折线段间相互位置关系的一系列概念。提出通过两条折线段之间的位置关系和点与折线段的位置关系等进行折线段的多笔画判定,并给出详细的聚类算法。最后通过自主开发的FSR系统对提出的算法加以验证。     

New grouping and fitting methods for interactive overtraced sketches

This paper describes a new method for recognizing overtraced strokes to 2D geometric primitives, which are further interpreted as 2D line drawings. This method can support rapid grouping and fitting of overtraced polylines or conic curves based on the classified characteristics of each stroke during its preprocessing stage. The orientation and its endpoints of a classified stroke are used in the stroke grouping process. The grouped strokes are then fitted with 2D geometry. This method can deal with overtraced sketch strokes in both solid and dash linestyles, fit grouped polylines as a whole polyline and simply fit conic strokes without computing the direction of a stroke. It avoids losing joint information due to segmentation of a polyline into line-segments. The proposed method has been tested with our freehand sketch recognition system (FSR), which is robust and easier to use by removing some limitations embedded with most existing sketching systems which only accept non-overtraced stroke drawing. The test results showed that the proposed method can support freehand sketching based conceptual design with no limitations on drawing sequence, directions and overtraced cases while achieving a satisfactory interpretation rate.     

手绘草图的在线分段识别

提出了一种在线手绘草图快速分段识别方法。先对草绘笔划进行平滑预处理,以减少噪声干扰和冗余点的数目;然后利用草绘笔划的动静态特性,以及用户的草绘习惯等特性找出笔划的关键分段点,将笔划分为多个笔划子段;最后利用基于二次曲线的方法对笔划子段进行分段识别和特征参数计算,并通过构造面向对象的图形数据结构对识别出的几何图元进行重构。实例表明,该方法具有较好的识别能力和系统稳定性,能够应用于二维概念草图的快速表达,以及后续三维草绘建模的特征笔划智能识别过程中。     

Pencil-like sketch rendering of 3D scenes using trajectory planning and dynamic tracking

Objective: We present a new non-photorealistic rendering method to render 3D scenes in the form of pencil-like sketches.Methods: This work is based on the observation that the dynamic feedback mechanism involving the human visual system and the motor control of the hand collectively generates the visual characteristics unique to hand-drawn sketches. At the heart of our approach is a trajectory planning and tracking algorithm that generate the sketch in multiple layers using a dynamic pen model. On each layer, a set of target strokes are generated from the silhouette lines, edges, and shaded regions which serve as the target trajectory for a closed-loop dynamic pen model. The pen model then produces the rendered sketch, whose characteristics can be adjusted with a set of trajectory and tracking parameters. This process continues in several layers until the tonal difference between the sketch and the original 3D render is minimized.Results: We demonstrate our approach with examples that are created by controlling the parameters of our sketch rendering algorithms.Conclusion: The examples not only show typical sketching artifacts that are common to human-drawn sketches but also demonstrate that it is capable of producing multiple sketching styles.     

基于时序特征的草图识别方法

草图识别是一项很具有挑战性的工作。目前,大部分草图识别的工作都将草图当作普通的纹理图像,忽视了草图的时序性。因此,文中通过挖掘草图的时序性,将草图笔画按照时间分组。为进一步利用时序特征在草图识别过程中的作用,使用了循环神经网络将笔画分组按照时间序列作为输入,最后使用联合贝叶斯将各个时序下获得的草图特征进行整合,完成草图的识别工作。在公开标准数据集上对所提算法进行了测试,实验结果显示该算法的识别准确率明显高于其他算法。     

基于深度学习的草图分割算法综述

草图一直是人类传递信息的重要工具之一.草图可以通过简单明了的形式更快地表达人类的一些复杂思想,因此,草图处理算法一直是计算机视觉领域的研究热点之一.目前,对草图的研究主要集中在识别、检索和补全等方面.随着研究者对于草图细粒度操作的重视,对草图分割方面的研究也得到越来越多的关注.近年来,随着深度学习与计算机视觉技术的发展,出现了大量基于深度学习的草图分割方法,草图分割的精确度和效率也都得到了较大提升.但是,由于草图自身的抽象性、稀疏性和多样性,草图分割仍然是一个非常具有挑战性的课题.对基于深度学习的草图分割算法进行整理、分类、分析和总结,首先阐述了3种基本的草图表示方法与常用的草图分割数据集,再按草图分割算法的预测结果分别介绍了草图语义分割、草图感知聚类与草图解析算法,然后在主要的数据集上收集与整理草图分割算法的评测结果并对结果进行分析,最后总结了草图分割相关的应用并探讨未来可能的发展方向.     

基于草图的面向概念设计的协同图表绘制工具

概念设计过程使用了多种图表来表示设计概念以及构建功能结构.将手绘草图作为设计者之间的一种通信语言引入到异地同步协同概念设计过程,提出了基于手绘草图的协同图表绘制多agent 系统,包含草图交互、草图识别、通信、协调等多个agent.讨论了各agent 之间的通信机制以及主要agent 的实现策略,包括草图识别以及语义一致性维护策略.将系统应用到协同流程图绘制领域,运行结果表明,该工具能够改善人机交互模式,促进多用户之间的交流和协作.     

基于草绘的机构识别及机构分析方法研究*

在概念设计阶段构造新型的支持创新过程的设计系统,对新产品的设计活动具有重要意义。在机械产品概念设计中将机构看成由图元构成的图形,提出一种面向概念设计的机构草图识别及分析方法,主要内容包括手绘草图输入及机构草图识别、机构方案运动分析。本文把手绘草图识别技术和机构运动相结合,通过对机构草图的识别以及机构的运动分析,实现在概念设计阶段对机构设计方案的评价分析。     

一种简单实用的草图编辑手势识别方法

联机草绘设计作为一种自然、高效的人机交互方式，继承了传统纸笔草绘设计的优点，弥补了现有CAD软件在处理模糊、不精确信息方面的不足，并日益受到人们的关注。针对联机草绘图形的编辑修改，设计出一套简单、快捷的编辑手势．并采用模式匹配的方法对其进行识别。实验结果表明，提出的方法具有较高的识别效果，加快了概念草图的设计过程。     

手绘草图实时处理方法研究

徒手草绘作为一种简便、自然、高效的人机交互方式,在计算机辅助设计领域越来越受到人们的重视。本文主要针对草绘设计与图形识别的行为过程进行了一系列较为广泛的研究,以便将用户的草绘习惯、识别能力与现有的CAD技术紧密结合起来,开发出新一代的智能CAD产品。具体包括草图前处理、特征点的检测、笔划分段、图元识别、图元重构、图元规整、端点校正等内容。实验表明所提出的方法能得到较好的识别结果。     

手绘草图实时处理方法研究

徒手草绘作为一种简便、自然、高效的人机交互方式，在计算机辅助设计领域越来越受到人们的重视。本文主要针对草绘设计与图形识别的行为过程进行了一系列较为广泛的研究，以便将用户的草绘习惯、识别能力与现有的CAD技术紧密结合起来，开发出新一代的智能CAD产品。具体包括草图前处理、特征点的检测、笔划分段、图元识别、图元重构、图元规整、端点校正等内容。实验表明所提出的方法能得到较好的识别结果。     

一种简单实用的草图编辑手势识别方法

联机草绘设计作为一种自然、高效的人机交互方式,继承了传统纸笔草绘设计的优点,弥补了现有CAD软件在处理模糊、不精确信息方面的不足,并日益受到人们的关注。针对联机草绘图形的编辑修改,设计出一套简单、快捷的编辑手势,并采用模式匹配的方法对其进行识别。实验结果表明,提出的方法具有较高的识别效果,加快了概念草图的设计过程。     

Extraction of line segments and circular arcs from freehand strokes based on segmental homogeneity features.

The extraction of component line segments and circular arcs from freehand strokes along with their relations is a prerequisite for sketch understanding. Existing approaches usually take three stages to segment a stroke: first identifying segmentation points, then classifying the substroke between each pair of adjacent segmentation points, and, finally, obtaining graphical representations of substrokes by fitting graphical primitives to them. Since a stroke inevitably contains noises, the first stage may produce wrong or inaccurate segmentation points, resulting in the wrong substroke classification in the second stage and inaccurately fitted parameters in the third stage. To overcome the noise sensitivity of the three-stage method, the segmental homogeneity feature is emphasized in this paper. We propose a novel approach, which first extracts graphical primitives from a stroke by a connected segment growing from a seed-segment and then utilizes relationships between the primitives to refine their control parameters. We have conducted experiments using real-life strokes and compared the proposed approach with others. Experimental results demonstrate that the proposed approach is effective and robust.     

融合深度学习和语义树的草图识别方法

现有的草图识别框架利用整幅图像作为网络输入,草图识别过程可解释性较差.文中融合深度学习和语义树,提出草图语义网(Sketch-Semantic Net).首先对草图进行部件分割,将单幅完整的草图分割为多个具有语义概念的部件图.然后利用深度迁移学习识别草图部件.最后通过语义树的语义概念关联部件同部件所属草图对象类别,较好地弥补sketch图像从底层语义到高层语义之间的语义鸿沟.在广泛应用的草图分割数据集上的实验验证文中方法的有效性.     

基于描绘单幅图像的三维树木交互建模系统

为了提高树木建模的真实感与可交互性,提出了一种基于单幅树木图像或直接手绘的交互式植物建模系统。系统根据植物形态学规律构建了标准三维树木的模板。通过描绘图像中树的主要枝干,结合叶序周规律,基于三维模板树将其从二维图像变换到三维模型,并通过弯曲、增加和删除枝干以及添加树叶等交互式操作生成和修改三维树木模型。实验结果表明,该系统能便捷快速地生成真实感较强的三维树木。     

SmartCanvas: Context‐inferred Interpretation of Sketches for Preparatory Design Studies

In early or preparatory design stages, an architect or designer sketches out rough ideas, not only about the object or structure being considered, but its relation to its spatial context. This is an iterative process, where the sketches are not only the primary means for testing and refining ideas, but also for communicating among a design team and to clients. Hence, sketching is the preferred media for artists and designers during the early stages of design, albeit with a major drawback: sketches are 2D and effects such as view perturbations or object movement are not supported, thereby inhibiting the design process. We present an interactive system that allows for the creation of a 3D abstraction of a designed space, built primarily by sketching in 2D within the context of an anchoring design or photograph. The system is progressive in the sense that the interpretations are refined as the user continues sketching. As a key technical enabler, we reformulate the sketch interpretation process as a selection optimization from a set of context‐generated canvas planes in order to retrieve a regular arrangement of planes. We demonstrate our system (available at http:/geometry.cs.ucl.ac.uk/projects/2016/smartcanvas/ ) with a wide range of sketches and design studies.     

基于保特征调和场的交互式网格分片

网格模型分片在计算机图形学应用中具有重要意义,本文提出了一种基于网格上的调和场和图割技术的网格模型分片算法.用户可以通过划线的方式来指定网格上感兴趣的区域;算法自动构建反映该区域细节特征的调和场,进而采用图割技术,得到满足用户要求的分片结果;通过对网格分割边界的光滑处理,可有效改善锯齿型分割边界.实验结果表明,我们的算法对于特征单一或复杂的网格模型都能得到符合用户意图的分割结果.