Yu-Kun Lai

Senior Lecturer
Visual Computing Group
School of Computer Science and Informatics
Cardiff University, Wales, UK

Contact Info

Office: S/3.06 Queen's Buildings, 5 The Parade, Roath, Cardiff CF24 3AA
Tel: +44 (0) 29 20876353
Fax: +44 (0) 29 20874598
Email: Yukun.Lai (at) cs.cardiff.ac.uk

Publications   Teaching    Prizes and Honours  Education      CV 


Professional Activities        

I'm on the editorial board of The Visual Computer.

I was conference co-chair of Computation Visual Media (CVM) 2016 and Eurographics Symposium on Geometry Processing (SGP) 2014.

I have been on the programme committee of

  • ACM Symposium on Solid and Physical Modeling (ACM SPM, SIAM GD/SPM) 2012, 2013, 2014, 2015, 2016
  • Geometric Modeling and Processing (GMP) 2012, 2014, 2015, 2016
  • SIGGRAPH Asia Technical Briefs & Posters 2014, 2015, 2016
  • Expressive 2014, 2015, 2016
  • Pacific Graphics (PG) 2012, 2015, 2016
  • Eurographics Symposium on Geometry Processing (SGP) 2014, 2015
  • CAD/Graphics 2011, 2013, 2015
  • Computational Visual Media (CVM) 2012, 2013, 2015, 2017
  • British Machine Vision Conference 2015
  • Eurographics 2011 short papers
  • Computer Animation and Social Agents (CASA) 2010

I'm also a regular reviewer for major journals/conferences in computer graphics and geometric modelling.

 

Research Interests

  • Computer Graphics
  • Geometry Processing
  • Computer Vision
  • Image Processing
  • Computer-Aided Geometric Design

In other words, my research interests include creating nice images/shapes/animation automatically or with a small amount of user interaction and developing automatic algorithms to understand and analyse visual data and present data in an interesting manner. My recent work is briefly summarised below:

If you are an undergraduate or master student interested in doing research in these exciting and highly rewarded fields, send me an email.

Some potential projects (but more are possible).

  • Image and Video Vectorisation
  • 3D Model Segmentation and Analysis
  • Modelling and Transferring Geometric Details over 3D Shapes


Teaching Activities

I teach the following modules in the academic year 2015/16:

  • CM1208 Maths for Computer Science
  • CM2104 Computational Mathematics (shared with Prof. A. D. Marshall)
  • CM2208 Scientific Computing (shared with Prof. A. D. Marshall)
  • CMT205 Object Oriented Development with Java (shared with Prof. A. D. Marshall)
Publications            2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 Top

2016


Efficient and Flexible Deformation Representation for Data-Driven Surface Modeling
ACM Transactions on Graphics, to appear. (to be presented at SIGGRAPH 2016)  
Lin Gao, Yu-Kun Lai, Dun Liang, Shu-Yu Chen and Shihong Xia

Effectively characterizing the behavior of deformable objects has wide applicability but remains challenging. We present a new rotation invariant deformation representation and a novel reconstruction algorithm to accurately reconstruct the positions and local rotations simultaneously. Meshes can be very efficiently reconstructed from our representation by matrix predecomposition, while at the same time, hard or soft constraints can be flexibly specified with only positions of handles needed. Our approach is thus particularly suitable for constrained deformations guided by examples, providing significant benefits over state-of-the-art methods. Based on this, we further propose novel data-driven approaches to mesh deformation and nonrigid registration of deformable objects. Both problems are formulated consistently as finding an optimized model in the shape space that satisfies boundary constraints, either specified by the user, or according to the scan. By effectively exploiting the knowledge in the shape space, our method produces realistic deformation results in real-time and produces high quality registrations from a template model to a single noisy scan captured using a low-quality depth camera, outperforming state-of-the-art methods.


Other Publications:

2015


Active Exploration of Large 3D Model Repositories
IEEE Transactions on Visualization and Computer Graphics, vol. 21(12), pp. 1390-1402, 2015 (doi:10.1109/TVCG.2014.2369039).  
Lin Gao, Yan-Pei Cao, Yu-Kun Lai, Hao-Zhi Huang, Leif Kobbelt, Shi-Min Hu

With broader availability of large-scale 3D model repositories, the need for efficient and effective exploration becomes more and more urgent. Existing model retrieval techniques do not scale well with the size of the database since often a large number of very similar objects are returned for a query, and the possibilities to refine the search are quite limited. We propose an interactive approach where the user feeds an active learning procedure by labeling either entire models or parts of them as "like" or "dislike" such that the system can automatically update an active set of recommended models. To provide an intuitive user interface, candidate models are presented based on their estimated relevance for the current query. From the methodological point of view, our main contribution is to exploit not only the similarity between a query and the database models but also the similarities among the database models themselves. We achieve this by an offline pre-processing stage, where global and local shape descriptors are computed for each model and a sparse distance metric is derived that can be evaluated efficiently even for very large databases. We demonstrate the effectiveness of our method by interactively exploring a repository containing over 100K models.


Other Publications:

2014


Automatic Semantic Modeling of Indoor Scenes from Low-quality RGB-D Data using Contextual Information
ACM Transactions on Graphics, vol. 33(6), 208:1-12, 2014 (SIGGRAPH Asia 2014).  Project
Kang Chen, Yu-Kun Lai, Yu-Xin Wu, Ralph R. Martin, Shi-Min Hu

We present a novel solution to automatic semantic modeling of indoor scenes from a sparse set of low-quality RGB-D images. We exploit the knowledge in a scene database containing hundreds of indoor scenes and over 10,000 objects represented as manually segmented and labeled mesh models. Within a few seconds, we output a visually plausible 3D scene, based on models and parts from the database adapted to fit the input scans. Using low-quality RGBD data is challenging due to noise, low resolution, occlusion and missing depth information. Contextual relationships learned from the 3D database are used to constrain reconstruction, ensuring semantic compatibility between both object models and parts. Small objects and objects with incomplete depth information are difficult to recover reliably. We do so with a two-stage approach: major objects are recognized first to provide a known scene structure. We then apply 2D contour-based model retrieval to recover the smaller objects. An evaluation on our own data and two public RGB-D datasets shows that our approach can model typical real-world indoor scenes efficiently and robustly.


BiggerPicture: Data-driven Image Extrapolation Using Graph Matching
ACM Transactions on Graphics, vol. 33(6), 173:1-13, 2014 (SIGGRAPH Asia 2014).  Project
Miao Wang, Yu-Kun Lai, Yuan Liang, Ralph R. Martin, Shi-Min Hu

Filling a small hole in an image with plausible content is well studied. Extrapolating an image to give a distinctly larger one is much more challenging---a significant amount of additional content is needed which matches the original image, especially near its boundaries. We propose a data-driven approach to this problem. Given a source image, and the amount and direction(s) in which it is to be extrapolated, our system determines visually consistent content for the extrapolated regions using library images. As well as considering low-level matching, we achieve consistency at a higher level by using graph proxies for regions of source and library images. Treating images as graphs allows us to find candidates for image extrapolation in a feasible time. Consistency of subgraphs in source and library images is used to find good candidates for the additional content; these are then further filtered. Region boundary curves are aligned to ensure consistency where image parts are joined using a photomontage method. We demonstrate the power of our method in image editing applications.


Diffusion Pruning for Rapidly and Robustly Selecting Global Correspondences using Local Isometry
ACM Transactions on Graphics, vol. 33(1), Article No. 4, pp. 1-17, 2014.
Gary K.L. Tam, Ralph R. Martin, Paul L. Rosin and Yu-Kun Lai

Finding correspondences between two surfaces is a fundamental operation in various applications in computer graphics and related fields. Candidate correspondences can be found by matching local signatures, but as they only consider local geometry, many are globally inconsistent. We provide a novel algorithm to prune a set of candidate correspondences to those most likely to be globally consistent. Our approach can handle articulated surfaces, and ones related by a deformation which is globally non-isometric, provided that the deformation is locally approximately isometric. Our approach uses an efficient diffusion framework, and only requires geodesic distance calculations in small neighbourhoods, unlike many existing techniques which require computation of global geodesic distances. We demonstrate that, for typical examples, our approach provides significant improvements in accuracy, yet also reduces time and memory costs by a factor of several hundred compared to existing pruning techniques. Our method is furthermore insensitive to holes, unlike many other methods.


Parametric Meta-Filter Modeling from a Single Example Pair
The Visual Computer, vol. 30(6-8), pp. 673--684, 20014    Project
Shi-Sheng Huang, Guo-Xin Zhang, Yu-Kun Lai, Johannes Kopf, Daniel Cohen-Or, Shi-Min Hu

We present a method for learning a meta-Filter from an example pair comprising an original image A and its Filtered version A0 using an unknown image Filter. A meta-Filter is a parametric model, consisting of a spatially varying linear combination of simple basis Filters. We introduce a technique for learning the parameters of the meta-Filter f such that it approximates the effects of the unknown Filter, i.e., f(A) approximates A0. The meta-Filter can be transferred to novel input images, and its parametric representation enables intuitive tuning of its parameters to achieve controlled variations. We show that our technique successfully learns and models meta-Filters that approximate a large variety of common image Filters with high accuracy both visually and quantitatively.


Efficient Circular Thresholding
IEEE Transactions on Image Processing, vol. 23(3), pp. 992-1001, 20014 code
Yu-Kun Lai and Paul L. Rosin

Otsu's algorithm for thresholding images is widely used, and the computational complexity of determining the threshold from the histogram is O(N) where N is the number of histogram bins. When the algorithm is adapted to circular rather than linear histograms then two thresholds are required for binary thresholding. We show that, surprisingly, it is still possible to determine the optimal threshold in O(N) time. The efficient optimal algorithm is over 300 times faster than traditional approaches for typical histograms and is thus particularly suitable for real-time applications. We further demonstrate the usefulness of circular thresholding using the adapted Otsu criterion for various applications, including analysis of optical flow data, indoor/outdoor image classification and non-photorealistic rendering. In particular, by combining circular Otsu feature with other colour/texture features, a 96.9% correct rate is obtained for indoor/outdoor classification on the well known IITM-SCID2 dataset, outperforming the state-of-the-art result by 4.3%.


Other Publications:

2013


A Data-Driven Approach to Realistic Shape Morphing
Computer Graphics Forum, vol. 32(2), 449-457, 2013 (Eurographics 2013).
Lin Gao, Yu-Kun Lai, Qixing Huang and Shi-Min Hu

Morphing between 3D objects is a fundamental technique in computer graphics. Traditional methods of shape morphing focus on establishing meaningful correspondences and finding smooth interpolation between shapes. Such methods however only take geometric information as input and thus cannot in general avoid producing unnatural interpolation, in particular for large-scale deformations. This paper proposes a novel data-driven approach for shape morphing. Given a database with various models belonging to the same category, we treat them as data samples in the plausible deformation space. These models are then clustered to form local shape spaces of plausible deformations. We use a simple metric to reasonably represent the closeness between pairs of models. Given source and target models, the morphing problem is casted as a global optimization problem of finding a minimal distance path within the local shape spaces connecting these models. Under the guidance of intermediate models in the path, an extended as-rigid-as-possible interpolation is used to produce the final morphing. By exploiting the knowledge of plausible models, our approach produces realistic morphing for challenging cases as demonstrated by various examples in the paper.


Generalized Anisotropic Stratified Surface Sampling
IEEE Transactions on Visualization and Computer Graphics, vol. 19(7), 1143-1157, 2013.
Jon Quinn, Frank Langbein, Yu-Kun Lai and Ralph Martin

We introduce a novel stratified sampling technique for mesh surfaces that gives the user control over sampling density and anisotropy via a tensor field. Our approach is based on sampling space-filling curves mapped onto mesh segments via parametrizations aligned with the tensor field. After a short pre-processing step, samples can be generated in real-time. Along with visual examples, we provide rigorous spectral analysis and differential domain analysis of our sampling. The sample distributions are of high quality: they fulfil the blue noise criterion, so have minimal artifacts due to regularity of sampling patterns, and they accurately represent isotropic and anisotropic densities on the plane and on mesh surfaces. They also have low discrepancy, ensuring that the surface is evenly covered.


Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Non-Rigid
IEEE Transactions on Visualization and Computer Graphics, vol. 19(7), 1199-1217, 2013.
Gary Tam, Zhi-Quan Cheng, Yu-Kun Lai, Frank Langbein, Yonghuai Liu, David Marshall, Ralph Martin, Xianfang Sun and Paul Rosin

3D surface registration transforms multiple 3D datasets into the same coordinate system so as to align overlapping components of these sets. Recent surveys have covered different aspects of either rigid or non-rigid registration, but seldom discuss them as a whole. Our study serves two purposes: (i) to give a comprehensive survey of both types of registration, focusing on 3D point clouds and meshes, and (ii) to provide a better understanding of registration from the perspective of data fitting. Registration is closely related to data fitting in that it comprises three core interwoven components: model selection, correspondences & constraints and optimization. Study of these components (i) provides a basis for comparison of the novelties of different techniques, (ii) reveals the similarity of rigid and non-rigid registration in terms of problem representations, and (iii) shows how over-fitting arises in non-rigid registration and the reasons for increasing interest in intrinsic techniques. We further summarise some practical issues of registration which include initializations and evaluations, and discuss some of our own observations, insights and foreseeable research trends.


Efficient Synthesis of Gradient Solid Textures
Graphical Models, vol. 75(3), 104-117, 2013.
Guo-Xin Zhang, Yu-Kun Lai and Shi-Min Hu
Preliminary version appears in Proc. Computational Visual Media 2012.

Solid textures require large storage and are computationally expensive to synthesize. In this paper, we propose a novel solid representation called gradient solids to compactly represent solid textures, including a tricubic interpolation scheme of colors and gradients for smooth variation and a region-based approach for representing sharp boundaries. We further propose a novel approach to directly synthesize gradient solid textures from exemplars. Compared to existing methods, our approach avoids the expensive step of synthesizing the complete solid textures at voxel level and produces optimized solid textures using our representation. This avoids significant amount of unnecessary computation and storage involved in the voxel-level synthesis while producing solid textures with comparable quality to the state of the art. The algorithm is much faster than existing approaches for solid texture synthesis and makes it feasible to synthesize high-resolution solid textures in full. We also propose a novel application — instant editing propagation on full solids.


Example-based Color Transfer for Gradient Meshes
IEEE Transactions on Multimedia, vol. 15(3), pp. 549-560, 2013.
Yi Xiao, Liang Wan, Chi-Sing Leung, Yu-Kun Lai and Tien-Tsin Wong

Editing a photo-realistic gradient mesh is a tough task. Even only editing the colors of an existing gradient mesh can be exhaustive and time-consuming. To facilitate user-friendly color editing, we develop an example-based color transfer method for gradient meshes, which borrows the color characteristics of an example image to a gradient mesh. We start by exploiting the constraints of the gradient mesh, and accordingly propose a linear-operator-based color transfer framework. Our framework operates only on colors and color gradients of the mesh points and preserves the topological structure of the gradient mesh. Bearing the framework in mind, we build our approach on PCA-based color transfer. After relieving the color range problem, we incorporate a fusion-based optimization scheme to improve color similarity between the reference image and the recolored gradient mesh. Finally, a multi-swatch transfer scheme is provided to enable more user control. Our approach is simple, effective, and much faster than color transferring the rastered gradient mesh directly. The experimental results also show that our method can generate pleasing recolored gradient meshes.


Other Publications:

2012


Improved Initialisation for Centroidal Voronoi Tessellation and Optimal Delaunay Triangulation
Computer-Aided Design, vol. 44(11), pp. 1062-1071, 2012.
Jonathan A. Quinn, Feng Sun, Frank C. Langbein, Yu-Kun Lai, Wenping Wang and Ralph R. Martin

Centroidal Voronoi tessellations and optimal Delaunay triangulations can be approximated efficiently by non-linear optimisation algorithms. This paper demonstrates that the point distribution used to initialise the optimisation algorithms is important. Compared to conventional random initialisation, certain low-discrepancy point distributions help convergence towards more spatially regular results and require fewer iterations for planar and volumetric tessellations.


Vertex Location Optimisation for Improved Remeshing
Graphical Models, vol. 74(4), pp. 233-243, 2012.
Yu-Kun Lai and Ralph R. Martin

Remeshing aims to produce a more regular mesh from a given input mesh, while representing the original geometry as accurately as possible. Many existing remeshing methods focus on where to place new mesh vertices; these samples are placed exactly on the input mesh. However, considering the output mesh as a piecewise linear approximation of some geometry, this simple scheme leads to significant systematic error in nonplanar regions. Here, we use parameterised meshes and the recent mathematical development of orthogonal approximation using Sobolev-type inner products to develop a novel sampling scheme which allows vertices to lie in space near the input surface, rather than exactly on it. The algorithm requires little extra computational effort and can be readily incorporated into many remeshing approaches. Experimental results show that on average, approximation error can be reduced by 40% with the same number of vertices. A similar technique can also be applied to surface normals to provide more accurate rendering results with the same number of vertices.


Lp Shape Deformation
Science China Information Sciences, vol. 55(5), pp. 983-993, 2012.
Lin Gao, Guo-Xin Zhang and Yu-Kun Lai

Shape deformation is a fundamental tool in geometric modeling. Existing methods consider preserving local details by minimizing some energy functional measuring local distortions in the L2 norm. This strategy distributes distortions quite uniformly to all the vertices and penalizes outliers. However, there is no unique answer for a natural deformation as it depends on the nature of the objects. Inspired by recent sparse signal reconstruction work with non L2 norm, we introduce general Lp norms to shape deformation; the positive parameter p provides the user with a flexible control over the distribution of unavoidable distortions. Compared with the traditional L2 norm, using smaller p, distortions tend to be distributed to a sparse set of vertices, typically in feature regions, thus making most areas less distorted and structures better preserved. On the other hand, using larger p tends to distribute distortions more evenly across the whole model. This flexibility is often desirable as it mimics objects made up with different materials. By specifying varying p over the shape, more flexible control can be achieved. We demonstrate the effectiveness of the proposed algorithm with various examples.


2011


Sketch Guided Solid Texturing
Graphical Models, vol. 73(3), pp. 59-73, 2011.
Guo-Xin Zhang, Song-Pei Du, Yu-Kun Lai, Tianyun Ni and Shi-Min Hu

Compared to 2D textures, solid textures offer the advantage of consistently representing not only the bounding surfaces of objects, but also their interiors. Existing solid texture synthesis methods pay little attention to the generation of conforming textures that capture essential geometric structures or accurately reflect the artists&apos design intentions. In this paper, we propose a novel approach to synthesizing solid textures using 2D exemplar texture images. The generated textures locally agree with a tensor field derived from a few user sketching curves. We use a deterministic approach such that only a small portion of the voxels needs to be synthesized on demand. Correction is the fundamental step in deterministic texture synthesis to update each voxel according to its local neighborhood. We propose a novel history windows representation, which is general enough to represent various previous correction schemes in a unified manner, and a novel dual grid correction scheme based on the representation to significantly reduce the dependent voxels while still producing high quality results. Experimental results demonstrate that our method produces significantly improved solid textures with a very small amount of user interaction.


2010


Metric Driven RoSy Field Design and Remeshing
IEEE Transactions on Visualization and Computer Graphics, vol. 16(1), pp. 95-108, 2010.
Yu-Kun Lai, Miao Jin, Xuexiang Xie, Ying He, Jonathan Palacios, Eugene Zhang, Shi-Min Hu and Xianfeng David Gu

Designing rotational symmetries on surfaces is an important task for a wide range of graphics applications. This work introduces a rigorous and practical algorithm for automatic N-RoSy design on arbitrary surfaces with user defined field topologies. The user has full control of the number, positions and indices of the singularities, the turning numbers of the loops, and is able to edit the field interactively.



Feature Aligned Quad Dominant Remeshing using Iterative Local Updates
Computer-Aided Design, vol. 42(2), pp. 109-117, 2010.
Yu-Kun Lai, Leif Kobbelt and Shi-Min Hu
Preliminary version appears in Proc. ACM Solid and Physical Modeling 2008.

In this paper we present a new algorithm which turns an unstructured triangle mesh into a quad-dominant mesh with edges well aligned to the principal directions of the underlying surface. Instead of computing a globally smooth parameterization or integrating curvature lines along a tangent vector field, we simply apply an iterative relaxation scheme which incrementally aligns the mesh edges to the principal directions. We further obtain the quad-dominant mesh by dropping the not-aligned diagonal edges from the triangle mesh. A post-processing stage is introduced to further improve the results. The major advantage of our algorithm is its conceptual simplicity since it is merely based on elementary mesh operations such as edge collapse, flip, and split. The resulting meshes exhibit a very good alignment to surface features and rather uniform distribution of mesh vertices. This makes them well-suited, e.g., as Catmull-Clark Subdivision control meshes.


Towards Artistic Minimal Rendering
ACM Symposium on Non Photorealistic Rendering, pp. 119-127, 2010. Try Online Demo
Paul L. Rosin and Yu-Kun Lai

Many nonphotorealistic rendering techniques exist to produce artistic effects from given images. Inspired by various artistic work such as Warhol's, interesting artistic effects can be produced by using a minimal rendering, where the minimum refers to the number of tones as well as the number and complexity of the primitives used for rendering. To achieve this goal, based on various computer vision techniques, our method uses a combination of refined lines and blocks, as well as a small number of tones, to produce abstracted artistic rendering with sufficient elements from the original image. There is always a trade-off between reducing the amount of information and the ability to represent the shape and details of the original images. Judging the level of abstraction is semantic-based, so we believe that giving users this flexibility is probably a good choice. By changing some intuitive parameters, a wide range of visually pleasing results can be produced. Our method is usually fully automatic, but a small amount of user interaction can optionally be incorporated to obtain selective abstraction.



Harmonic Field Based Volume Model Construction from Triangle Soup
Journal of Computer Science and Technology, vol. 25(3), pp. 562-571, 2010.
Chao-Hui Shen, Guo-Xin Zhang, Yu-Kun Lai, Shi-Min Hu and R. R. Martin

Surface triangle meshes and volume data are two commonly used representations of digital geometry. Converting from triangle meshes to volume data is challenging, since triangle meshes often contain defects such as small holes, internal structures, or self-intersections. In the extreme case, we may be simply presented with a set of arbitrarily connected triangles, a "triangle soup". This paper presents a novel method to generate volume data represented as an octree from a general 3D triangle soup. Our motivation is the Faraday cage from electrostatics. We consider the input triangles as forming an approximately closed Faraday cage, and set its potential to zero. We then introduce a second conductor surrounding it, and give it a higher constant potential. Due to the electrostatic shielding e®ect, the resulting electric field approximately lies in that part of space outside the shape implicitly determined by the triangle soup. Unlike previous approaches, our method is insensitive to small holes and internal structures, and is observed to generate volumes with low topological complexity. While our approach is somewhat limited in accuracy by the requirement of filling holes, it is still useful, for example, as a preprocessing step for applications such as mesh repair and skeleton extraction.

2009



Automatic and Topology Preserving Gradient Mesh Generation for Image Vectorization
ACM SIGGRAPH 2009, ACM Transactions on Graphics 28(3), Article No. 85.
Yu-Kun Lai, Shi-Min Hu and Ralph R. Martin

Gradient mesh vector graphics representation, used in commercial software, is a regular grid with specified position and color, and their gradients, at each grid point. Gradient meshes can compactly represent smoothly changing data, and are typically used for single objects. This paper advances the state of the art for gradient meshes in several significant ways. Firstly, we introduce a topology-preserving gradient mesh representation which allows an arbitrary number of holes. This is important, as objects in images often have holes, either due to occlusion, or their 3D structure. Secondly, our algorithm uses the concept of image manifolds, adapting surface parameterization and fitting techniques to generate the gradient mesh in a fully automatic manner. Existing gradient-mesh algorithms require manual interaction to guide grid construction, and to cut objects with holes into disk-like regions. Our new algorithm is empirically at least 10 times faster than previous approaches. Furthermore, image segmentation can be used with our new algorithm to provide automatic gradient mesh generation for a whole image. Finally, fitting errors can be simply controlled to balance quality with storage.

Rapid and Effective Segmentation of 3D Models using Random Walks
Computer Aided Geometric Design, vol. 26(6), pp. 665-679, 2009.
Yu-Kun Lai, Shi-Min Hu, Ralph R. Martin and Paul L. Rosin
Preliminary version appears in Proc. ACM Solid and Physical Modeling 2008.

3D models are now widely available for use in various applications. The demand for automatic model analysis and understanding is ever increasing. Model segmentation is an important step towards model understanding, and acts as a useful tool for different model processing applications, e.g. reverse engineering and modeling by example. We extend a random walk method used previously for image segmentation to give algorithms for both interactive and automatic model segmentation. This method is extremely efficient, and scales almost linearly with the number of faces, and the number of regions. For models of moderate size, interactive performance is achieved with commodity PCs. We demonstrate that this method can be applied to both triangle meshes and point cloud data. It is easy-to-implement, robust to noise in the model, and yields results suitable for downstream applications for both graphical and engineering models.



Stripification of Free-Form Surfaces with Global Error Bounds for Developable Approximation
IEEE Transactions on Automation Science and Engineering, vol. 6(4), pp. 700-709, 2009. videocode
Yon-Jin Liu, Yu-Kun Lai and Shi-Min Hu

Developable surfaces have many desired properties in manufacturing process. Since most existing CAD systems utilize tensor-product parametric surfaces including B-splines as design primitives, there is a great demand in industry to convert a general free-form parametric surface within a prescribed global error bound into developable patches. In this work we propose a practical and efficient solution to approximate a rectangular parametric surface with a small set of C^0-joint developable strips. The key contribution of the proposed algorithm is that, several optimization problems are elegantly solved in a sequence that offers a controllable global error bound on the developable surface approximation. Experimental results are presented to demonstrate the effectiveness and stability of the proposed algorithm.


Robust Principal Curvatures using Feature Adapted Integral Invariants
SIAM/ACM Joint Conference on Geometric and Physical Modeling, pp. 325-330, 2009.
Yu-Kun Lai, Shi-Min Hu and Fang Tong

3D models are now widely available for use in various applications. The demand for automatic model analysis and understanding is ever increasing. Model segmentation is an important step towards model understanding, and acts as a useful tool for different model processing applications, e.g. reverse engineering and modeling by example. We extend a random walk method used previously for image segmentation to give algorithms for both interactive and automatic model segmentation. This method is extremely efficient, and scales almost linearly with the number of faces, and the number of regions. For models of moderate size, interactive performance is achieved with commodity PCs. We demonstrate that this method can be applied to both triangle meshes and point cloud data. It is easy-to-implement, robust to noise in the model, and yields results suitable for downstream applications for both graphical and engineering models.

2008



Fairing Wireframes in Industrial Surface Design
IEEE International Conference on Shape Modeling and Applications, pp. 29-35, 2008.
Yu-Kun Lai, Yong-Jin Liu, Yu Zang and Shi-Min Hu

Wireframe is a modeling tool widely used in industrial geometric design. The term wireframe refers to two sets of curves, with the property that each curve from one set intersects with each curve from the other set. Akin to the u-, v-isocurves in a tensor-product surface, the two sets of curves in a wireframe span an underlying surface. In many industrial design activities, wireframes are usually set up and adjusted by the designers before the whole surfaces are reconstructed. For adjustment, the fairness of wireframe has a direct influence on the quality of the underlying surface. Wireframe fairing is significantly different from fairing individual curves in that intersections should be preserved and kept in the same order. In this paper, we first present a technique for wireframe fairing by fixing the parameters during fairing. The limitation of fixed parameters is further released by an iterative gradient descent optimization method with step-size control. Experimental results show that our solution is efficient, and produces reasonably fairing results of the wireframes.

Note on Industrial Applications of Hu's Surface Extension Algorithm
Geometric Modeling Processing, pp. 304-314, 2008.
Zang Yu, Yong-Jin and Yu-Kun Lai

An important surface modeling problem in CAD is to connect two disjoint B-spline patches with the second-order geometric continuity. In this paper we present a study to solve this problem based on the surface extension algorithm [Computer-Aided Design 2002; 34:415--419]. Nice properties of this extension algorithm are exploited in depth and thus make our solution very simple and efficient. Various practical examples are presented to demonstrate the usefulness and efficiency of our presented solution.

2007




Robust Feature Classification and Editing
IEEE Transactions on Visualization and Computer Graphics, vol. 13, Jan/Feb, pp. 34-45, 2007.
Yu-Kun Lai, Qian-Yi Zhou, Shi-Min Hu, Johannes Wallner and Helmut Pottmann

Sharp edges, ridges, valleys and prongs are critical for the appearance and an accurate representation of a 3D model. In this paper, we propose a novel approach that deals with the global shape of features in a robust way. Based on a remeshing algorithm which delivers an isotropic mesh in a feature sensitive metric, features are recognized on multiple scales via integral invariants of local neighborhoods. Morphological and smoothing operations are then used for feature region extraction and classification into basic types such as ridges, valleys and prongs. The resulting representation of feature regions is further used for feature-specific editing operations.


Developable Strip Approximation of Parametric Surfaces with Global Error Bounds
Pacific Graphics, pp. 441-444, 2007(poster).
Yong-Jin Liu, Yu-Kun Lai and Shi-Min Hu

Developable surfaces have many desired properties in manufacturing process. Since most existing CAD systems utilize parametric surfaces as the design primitive, there is a great demand in industry to convert a parametric surface within a prescribed global error bound into developable patches. In this work we propose a simple and efficient solution to approximate a general parametric surface with a minimum set of $C^0$-joint developable strips. The key contribution of the proposed algorithm is that, several global optimization problems are elegantly solved in a sequence that offers a controllable global error bound on the developable surface approximation. Experimental results are presented to demonstrate the effectiveness and stability of the proposed algorithm.

Principal curvatures from the integral invariant viewpoint
Computer Aided Geometric Design, vol. 24, pp. 428-442, 2007.
Helmut Pottmann, Johannes Wallner, Yong-Liang Yang, Yu-Kun Lai and Shi-Min Hu

The extraction of curvature information for surfaces is a basic problem of Geometry Processing. Recently an integral invariant solution of this problem was presented, which is based on principal component analysis of local neighbourhoods defined by kernel balls of various sizes. It is not only robust to noise, but also adjusts to the level of detail required. In the present paper we show an asymptotic analysis of the moments of inertia and the principal directions which are used in this approach. We also address implementation and, briefly, robustness issues and applications.

2006




Surface Fitting Based on a Feature Sensitive Parameterization

Computer-Aided Design, Vol. 38, No. 7, pp. 800-807, 2006.
Yu-Kun Lai, Shi-Min Hu and Helmut Pottmann

Most approaches to least squares fitting of a B-spline surface to measurement data require a parametrization of the data point set and the choice of suitable knot vectors. We propose to use uniform knots in connection with a feature sensitive parametrization. This parametrization allocates more parameter space to highly curved feature regions and thus automatically provides more control points where they are needed.


Surface Mosaics

The Visual Computer, vol. 22, no. 9-11, pp. 604-611, 2006 (Special issues of Pacific Graphics).
Yu-Kun Lai, Shi-Min Hu and Ralph R. Martin

This paper considers the problem of placing mosaic tiles on a surface to produce a surface mosaic. We assume that the user specifies a mesh model, the size of the tiles and the amount of grout, and optionally, a few control vectors at key locations on the surface indicating the preferred tile orientation at these points. From these inputs, we place equal-sized rectangular tiles over the mesh such as to almost cover it, with controlled orientation. The alignment of the tiles follows a vector field which is interpolated over the surface from the control vectors, and also forced into alignment with any sharp creases, open boundaries, and boundaries between regions of different colors. Our method efficiently solves the problem by posing it as one of globally optimizing a spring-like energy in the Manhattan metric, using overlapping local parameterizations.We demonstrate the effectiveness of our algorithm with various examples.


Feature Sensitive Mesh Segmentation
ACM Symposium on Solid and Physical Modeling, pp. 7-16, 2006.
Yu-Kun Lai, Shi-Min Hu and Ralph R. Martin

This paper considers the problem of placing mosaic tiles on a surface to produce a surface mosaic. We assume that the user specifies a mesh model, the size of the tiles and the amount of grout, and optionally, a few control vectors at key locations on the surface indicating the preferred tile orientation at these points. From these inputs, we place equal-sized rectangular tiles over the mesh such as to almost cover it, with controlled orientation. The alignment of the tiles follows a vector field which is interpolated over the surface from the control vectors, and also forced into alignment with any sharp creases, open boundaries, and boundaries between regions of different colors. Our method efficiently solves the problem by posing it as one of globally optimizing a spring-like energy in the Manhattan metric, using overlapping local parameterizations.We demonstrate the effectiveness of our algorithm with various examples.


Robust Principal Curvatures on Multiple Scales
Eurographics Symposium on Geometry Processing, pp. 223-226, 2006.
Yong-Liang Yang, Yu-Kun Lai, Shi-Min Hu and Helmut Pottmann

Geometry processing algorithms often require the robust extraction of curvature information. We propose to achieve this with principal component analysis (PCA) of local neighborhoods, defined via spherical kernels centered on the given surface F. Intersection of a kernel ball Br or its boundary sphere Sr with the volume bounded by F leads to the so-called ball and sphere neighborhoods. Information obtained by PCA of these neighborhoods turns out to be more robust than PCA of the patch neighborhood Br \F previously used. The relation of the quantities computed by PCA with the principal curvatures of F is revealed by an asymptotic analysis as the kernel radius r tends to zero. This also allows us to define principal curvatures “at scale r” in a way which is consistent with the classical setting. The advantages of the new approach are discussed in a comparison with results obtained by normal cycles and local fitting; whereas the former method somewhat lacks in robustness, the latter does not achieve a consistent behavior at features on coarse scales. As to applications, we address computing principal curves and feature extraction on multiple scales.


2005




Geometric texture synthesis and transfer via geometry images
ACM Symposium on Solid and Physical Modeling, pp. 15-26, 2005.
Yu-Kun Lai, Shi-Min Hu, Xianfeng Gu and Ralph R. Martin

In this paper, we present an automatic method which can transfer geometric textures from one object to another, and can apply a manually designed geometric texture to a model. Our method is based on geometry images as introduced by Gu et al. The key ideas in this method involve geometric texture extraction, boundary consistent texture synthesis, discretized orientation and scaling, and reconstruction of synthesized geometry. Compared to other methods, our approach is efficient and easy-to-implement, and produces results of high quality.


Prizes and Honours         Top

  • National Excellent Doctoral Dissertation of China Award, 2010.
  • Excellent PhD Graduate, Dept. of Computer Science and Technology, Tsinghua University, 2008.
  • First-Class Excellent Doctoral Thesis, Tsinghua University, 2008.
  • Microsoft Fellowship, 2007.
  • First-Class Scholarship of Excellent Students in Tsinghua Univ. (Morgan Stanley Scholarship), 2006.
  • Excellet Graduate of Tsinghua University, 2003.
  • Excellent Bachelor Thesis, Tsinghua University, 2003.
  • First-Class Scholarship of Excellent Students in Tsinghua Univ. (Sony Scholarship), 2002.
  • Gold Medal in National Olympiad in Informatics (NOI) of China, 1998.

Education   Top

09/1999-07/2003 Dept. of Computer Science and Technology, Tsinghua University, China Bachelor Degree
09/2003-07/2006 Dept. of Computer Science and Technology, Tsinghua University, China Master Degree
09/2006-07/2008 Dept. of Computer Science and Technology, Tsinghua University, China Ph.D Degree

 

Visiting Experience Top

10/2007-04/2008        Center for Visual Computing, State University of New York at Stony Brook, Stony Brook, NY 11790, USA.

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