In this paper, we present a framework allowing users to interact with geometrically complex3 D deformable objects using(multiple) haptic devices based on an extended shape matching approach. There are two major challe...In this paper, we present a framework allowing users to interact with geometrically complex3 D deformable objects using(multiple) haptic devices based on an extended shape matching approach. There are two major challenges for haptic-enabled interaction using the shape matching method. The first is how to obtain a rapid deformation propagation when a large number of shape matching clusters exist. The second is how to robustly handle the collision response when the haptic interaction point hits the particlesampled deformable volume. Our framework extends existing multi-resolution shape matching methods,providing an improved energy convergence rate. This is achieved by using adaptive integration strategies to avoid insignificant shape matching iterations during the simulation. Furthermore, we present a new mechanism called stable constraint particle coupling which ensures consistent deformable behavior during haptic interaction. As demonstrated in our experimental results, the proposed method provides natural and smooth haptic rendering as well as efficient yet stable deformable simulation of complex models in real time.展开更多
In this article, we investigate the use of joint a-entropy for 3D ear matching by incorporating the local shape feature of 3D ears into the joint a-entropy. First, we extract a sut^cient number of key points from the ...In this article, we investigate the use of joint a-entropy for 3D ear matching by incorporating the local shape feature of 3D ears into the joint a-entropy. First, we extract a sut^cient number of key points from the 3D ear point cloud, and fit the neighborhood of each key point to a single-value quadric surface on product parameter regions. Second, we define the local shape feature vector of each key point as the sampling depth set on the parametric node of the quadric surface. Third, for every pair of gallery ear and probe ear, we construct the minimum spanning tree （MST） on their matched key points. Finally, we minimize the total edge weight of MST to estimate its joint a-entropy the smaller the entropy is, the more similar the ear pair is. We present several examples to demonstrate the advantages of our algorithm, including low time complexity, high recognition rate, and high robustness. To the best of our knowledge, it is the first time that, in computer graphics, the classical information theory of joint a-entropy is used to deal with 3D ear shape recognition.展开更多
To improve the bending load-carrying capacity （ BLCC） of under-matched butt joint under four-point bending load in the elastic stage, the shape design of the reinforcement is studied based on the theoretics of mecha...To improve the bending load-carrying capacity （ BLCC） of under-matched butt joint under four-point bending load in the elastic stage, the shape design of the reinforcement is studied based on the theoretics of mechanics of materials. The concept, criterion, realization condition and design proposal of equal bending load-carrying capacity （EBLCC） are put forward. The theoretical analysis results have been verified by the finite element method. The simulation results are coincident basically with the ones of theoretical analysis. The research results show that the shape design of the reinforcement of EBLCC can improve BLCC of under-matched butt joint and the unilateral-side type reinforcement can replace double-side symmetry展开更多
甲骨残片缀合一直是甲骨学研究中最急迫最具基础性的工作,它使得甲骨残片经过拼接,复原为更加完整的原始材料.尽管前人及同行曾提出若干计算机辅助的甲骨缀合方法,但这些方法缀合准确度不足,未能真正投入使用,并不能真正帮助专家解决甲...甲骨残片缀合一直是甲骨学研究中最急迫最具基础性的工作,它使得甲骨残片经过拼接,复原为更加完整的原始材料.尽管前人及同行曾提出若干计算机辅助的甲骨缀合方法,但这些方法缀合准确度不足,未能真正投入使用,并不能真正帮助专家解决甲骨缀合问题,导致当前的甲骨缀合工作仍旧依靠人工、依旧费时费力.为了更好地研究甲骨残片的机器缀合问题,本文使用一个较大规模甲骨缀合基准数据集OB-Rejoin,该数据集包含了约一千幅甲骨拓片图像,且融入了大量的甲骨学界已缀成果,用于算法评估.基于该数据集,本文设计了一种基于斜率变化量序列匹配的甲骨缀合算法(Slope United Sequence Matching for Oracle Bone Fragments Conjugation,SUM),该方法将甲骨残片的断边碴口图像匹配问题转化为数值型的序列数据和序列相似性比对问题,以将尚不够非常精密的计算机视觉领域的碴口图像匹配问题转换为数据科学领域较为成熟的序列数据相似性匹配问题.SUM将数值型的碴口序列数据进一步转换为斜率变化量序列和字符序列数据,最后利用字符序列的模糊匹配完成甲骨残片的碴口匹配.在实验环节,SUM算法与经典的序列相似性计算方法在精确率、召回率、漏检率方面进行了对比,并与两个较新的基于深度学习的序列匹配算法和形状匹配算法进行了性能对比.整体而言,SUM在OB-Rejoin数据集上的Top-15缀合召回率达到了95.181%,超越了对比算法.重要出土文献的精准复原本身是历史学和古文字研究中客观存在的重大现实需求,具有重要的史学价值和意义,因此,本文的研究成果,不但有助于解决甲骨残片的机器缀合问题,还对秦汉简牍和敦煌遗书等重要出土文献的精准复原具有重要的参考价值.展开更多
In 3D models retrieval, feature description and retrieval of non-rigid model face more complex problems due to the isometry transformation of itself. We introduce the hierarchical combination matching into the feature...In 3D models retrieval, feature description and retrieval of non-rigid model face more complex problems due to the isometry transformation of itself. We introduce the hierarchical combination matching into the feature comparison, and build a map between the divided regions of two models, and then achieve accurate feature matching based on patch-by-patch, which successfully introduces the spatial information into feature matching. Verified by experiment, the 3D model retrieval method proposed in this paper based on hierarchical combination matching can make sure more accurate feature matching, so as to enhance the precision of retrieval.展开更多
基金supported by the National Science Foundation under Grant No. 1012975
文摘In this paper, we present a framework allowing users to interact with geometrically complex3 D deformable objects using(multiple) haptic devices based on an extended shape matching approach. There are two major challenges for haptic-enabled interaction using the shape matching method. The first is how to obtain a rapid deformation propagation when a large number of shape matching clusters exist. The second is how to robustly handle the collision response when the haptic interaction point hits the particlesampled deformable volume. Our framework extends existing multi-resolution shape matching methods,providing an improved energy convergence rate. This is achieved by using adaptive integration strategies to avoid insignificant shape matching iterations during the simulation. Furthermore, we present a new mechanism called stable constraint particle coupling which ensures consistent deformable behavior during haptic interaction. As demonstrated in our experimental results, the proposed method provides natural and smooth haptic rendering as well as efficient yet stable deformable simulation of complex models in real time.
基金It was supported in part by the National Natural Science Foundation of China under Grant Nos. 61472170, 61170143, 60873110, and Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia under Grant No. ITSM201301. Acknowledgement The work presented in this paper was done during Xiao-Peng Sun＇s visit at the graphics group of Michigan State University. Thank University of North Dakota for the biometrics database, thank Dr. Yi-Ying Tong for helpful discussions and review, and thank the reviewers of CVM2015 for constructive comments.
文摘In this article, we investigate the use of joint a-entropy for 3D ear matching by incorporating the local shape feature of 3D ears into the joint a-entropy. First, we extract a sut^cient number of key points from the 3D ear point cloud, and fit the neighborhood of each key point to a single-value quadric surface on product parameter regions. Second, we define the local shape feature vector of each key point as the sampling depth set on the parametric node of the quadric surface. Third, for every pair of gallery ear and probe ear, we construct the minimum spanning tree （MST） on their matched key points. Finally, we minimize the total edge weight of MST to estimate its joint a-entropy the smaller the entropy is, the more similar the ear pair is. We present several examples to demonstrate the advantages of our algorithm, including low time complexity, high recognition rate, and high robustness. To the best of our knowledge, it is the first time that, in computer graphics, the classical information theory of joint a-entropy is used to deal with 3D ear shape recognition.
文摘To improve the bending load-carrying capacity （ BLCC） of under-matched butt joint under four-point bending load in the elastic stage, the shape design of the reinforcement is studied based on the theoretics of mechanics of materials. The concept, criterion, realization condition and design proposal of equal bending load-carrying capacity （EBLCC） are put forward. The theoretical analysis results have been verified by the finite element method. The simulation results are coincident basically with the ones of theoretical analysis. The research results show that the shape design of the reinforcement of EBLCC can improve BLCC of under-matched butt joint and the unilateral-side type reinforcement can replace double-side symmetry
文摘甲骨残片缀合一直是甲骨学研究中最急迫最具基础性的工作,它使得甲骨残片经过拼接,复原为更加完整的原始材料.尽管前人及同行曾提出若干计算机辅助的甲骨缀合方法,但这些方法缀合准确度不足,未能真正投入使用,并不能真正帮助专家解决甲骨缀合问题,导致当前的甲骨缀合工作仍旧依靠人工、依旧费时费力.为了更好地研究甲骨残片的机器缀合问题,本文使用一个较大规模甲骨缀合基准数据集OB-Rejoin,该数据集包含了约一千幅甲骨拓片图像,且融入了大量的甲骨学界已缀成果,用于算法评估.基于该数据集,本文设计了一种基于斜率变化量序列匹配的甲骨缀合算法(Slope United Sequence Matching for Oracle Bone Fragments Conjugation,SUM),该方法将甲骨残片的断边碴口图像匹配问题转化为数值型的序列数据和序列相似性比对问题,以将尚不够非常精密的计算机视觉领域的碴口图像匹配问题转换为数据科学领域较为成熟的序列数据相似性匹配问题.SUM将数值型的碴口序列数据进一步转换为斜率变化量序列和字符序列数据,最后利用字符序列的模糊匹配完成甲骨残片的碴口匹配.在实验环节,SUM算法与经典的序列相似性计算方法在精确率、召回率、漏检率方面进行了对比,并与两个较新的基于深度学习的序列匹配算法和形状匹配算法进行了性能对比.整体而言,SUM在OB-Rejoin数据集上的Top-15缀合召回率达到了95.181%,超越了对比算法.重要出土文献的精准复原本身是历史学和古文字研究中客观存在的重大现实需求,具有重要的史学价值和意义,因此,本文的研究成果,不但有助于解决甲骨残片的机器缀合问题,还对秦汉简牍和敦煌遗书等重要出土文献的精准复原具有重要的参考价值.
基金Supported by National Nature Science Foundation of China(61379106,61379082,61227802)Shandong Provincial Natural Science Foundation(ZR2013FM036,ZR2015FM011,ZR2015FM022)
文摘In 3D models retrieval, feature description and retrieval of non-rigid model face more complex problems due to the isometry transformation of itself. We introduce the hierarchical combination matching into the feature comparison, and build a map between the divided regions of two models, and then achieve accurate feature matching based on patch-by-patch, which successfully introduces the spatial information into feature matching. Verified by experiment, the 3D model retrieval method proposed in this paper based on hierarchical combination matching can make sure more accurate feature matching, so as to enhance the precision of retrieval.
