Selected Publications (See my pages on Google Scholar Citations and DBLP)


Kai Xu*, Lintao Zheng*, Zihao Yan, Guohang Yan, Eugene Zhang, Matthias Niessner, Oliver Deussen, Daniel Cohen-Or and Hui Huang, "Autonomous Reconstruction of Unknown Indoor Scenes Guided by Time-varying Tensor Fields," ACM Transactions on Graphics (SIGGRAPH Asia 2017), Conditionally accepted. (* co-first authors). [Paper, ??M | Slides, ??M | Project page | Code release on ROS]

Autonomous reconstruction of unknown scenes by a mobile robot inherently poses the question of balancing between exploration efficacy and reconstruction quality. We present a navigation-by-reconstruction approach to address this question, where moving paths of the robot are planned to account for both global efficiency for fast exploration and local smoothness to obtain high-quality scans. An RGB-D camera, attached to the robot arm, is dictated by the desired reconstruction quality as well as the movement of the robot itself. Our key idea is to harness a time-varying tensor field ...

Jun Li, Kai Xu*, Siddhartha Chaudhuri, Ersin Yumer, Hao Zhang and Leonidas Guibas, "GRASS: Generative Recursive Autoencoders for Shape Structures," ACM Transactions on Graphics (SIGGRAPH 2017), 36(4). (* corresponding author). [Paper, 10M | Slides, 3.9M | Project page | Code & data]

We introduce a novel neural network architecture for encoding and synthesis of 3D shapes, particularly their structures. Our key insight is that 3D shapes are effectively characterized by their hierarchical organization of parts, which reflects fundamental intra-shape relationships such as adjacency and symmetry. We develop a recursive neural net based autoencoder to map a flat, unlabeled, arbitrary part layout to a compact code. The code effectively captures the hierarchical structures of varying complexity despite being fixed-dimensional: an associated decoder maps a code back to a full hierarchy. The learned bidirectional mapping is further tuned using an adversarial setup to yield a generative model of plausible structures, from which novel structures can be sampled. Finally, our structure synthesis framework is augmented by a second trained module that produces fine-grained part geometry, conditioned on global and local structural context ...

Chenyang Zhu, Renjiao Yi, Wallace Lira, Ibraheem Alhashim, Kai Xu and Hao Zhang, "Deformation-Driven Shape Correspondence via Shape Recognition," ACM Transactions on Graphics (SIGGRAPH 2017), 36(4). [Paper, 31M | Project page | Code & data]

Many approaches to shape comparison and recognition start by establishing a shape correspondence. We “turn the table” and show that quality shape correspondences can be obtained by performing many shape recognition tasks. What is more, the method we develop computes a ne-grained, topology-varying part correspondence between two 3D shapes where the core evaluation mechanism only recognizes shapes globally. This is made possible by casting the part correspondence problem in a deformation-driven framework and relying on a data-driven “deformation energy” which rates visual similarity between deformed shapes and models from a shape repository. Our basic premise is that if a correspondence between two chairs (or airplanes, bicycles, etc.) is correct, then a reasonable deformation between the two chairs anchored on ...

Oussama Remil, Qian Xie, Xingyu Xie, Kai Xu and Jun Wang, "Data-Driven Sparse Priors of 3D Shapes," Computer Graphics Forum (Pacific Graphics 2017). To appear. [PDF, ??M]

We present a sparse optimization framework for extracting sparse shape priors from a collection of 3D models. Shape priors are defined as point-set neighborhoods sampled from shape surfaces which convey important information encompassing normals and local shape characterization. A 3D shape model can be considered to be formed with a set of 3D local shape priors, while most of them are likely to have similar geometry. Our key observation is that the local priors extracted from a family of 3D shapes lie in a very low-dimensional manifold. Consequently, a compact and informative subset of priors can be learned to efficiently encode all shapes of the same family ...

Oussama Remil, Qian Xie, Xingyu Xie, Kai Xu and Jun Wang, "Surface Reconstruction with Data-driven Exemplar Priors," Computer-Aided Design. To appear. [PDF, ??M]

We propose a framework to reconstruct 3D models from raw scanned points by learning the prior knowledge of a specific class of objects. Unlike previous work that heuristically specifies particular regularities and defines parametric models, our shape priors are learned directly from existing 3D models under a framework based on affinity propagation. Given a database of 3D models within the same class of objects, we build a comprehensive library of 3D local shape priors. We then formulate the problem to select as-few-as-possible priors from the library, referred to as exemplar priors. These priors are sufficient to represent the 3D shapes of the whole class of objects from where they are generated. By manipulating these priors, we can reconstruct geometrically faithful models ...


Kai Xu, Yifei Shi, Lintao Zheng, Junyu Zhang, Min Liu, Hui Huang, Hao Su, Daniel Cohen-Or and Baoquan Chen, "3D Attention-Driven Depth Acquisition for Object Identification," ACM Transactions on Graphics (SIGGRAPH Asia 2016), 35(6). [PDF, 12.5M | PPT, ??M | Project page | Code]

We address the problem of autonomous exploring unknown objects in a scene by consecutive depth acquisitions. The goal is to model the scene via identifying the objects online, from among a large collection of 3D shapes. Fine-grained shape identification demands a meticulous series of observations attending to varying views and parts of the object of interest. Inspired by the recent success of attention-based models for 2D recognition, we develop a 3D Attention Model that selects the best views to scan from, as well as the most informative regions in each view to focus on, to achieve efficient object recognition. The region-level attention leads to focus-driven features ...

Min Liu, Yifei Shi, Lintao Zheng and Kai Xu, "Recurrent 3D Attentional Networks for End-to-End Active Object Recognition in Cluttered Scenes," arXiv:1610.04308. [PDF, 2M]

Active vision is inherently attention-driven: The agent selects views of observation to best approach the vision task while improving its internal representation of the scene being observed. Inspired by the recent success of attention-based models in 2D vision tasks based on single RGB images, we propose to address the multi-view depth-based active object recognition using attention mechanism, through developing an end-to-end recurrent 3D attentional network. The architecture comprises of a recurrent neural network (RNN), storing and updating an internal representation, and two levels of spatial transformer units, guiding two-level attentions. Our model, trained with a 3D shape database, is able to iteratively attend to the best views targeting an object of interest for recognizing it, and focus on the object in each view for removing the background clutter ...

Jun Wang and Kai Xu, "Shape Detection from Raw LiDAR Data with Subspace Modeling," IEEE Transactions on Visualization and Computer Graphics (TVCG). Accepted. [PDF, 3.1M]

LiDAR scanning has become a prevalent technique for digitalizing large-scale outdoor scenes. However, the raw LiDAR data often contain imperfections, e.g., missing large regions, anisotropy of sampling density, and contamination of noise and outliers, which are the major obstacles that hinder its more ambitious and higher level applications in digital city modeling. Observing that 3D urban scenes can be locally described with several low dimensional subspaces, we propose to locally classify the neighborhoods of the scans to model the substructures of the scenes. The key enabler is the adaptive kernel-scale scoring, filtering and clustering of substructures, making it possible to recover the local structures at all points simultaneously, even in the presence of severe data imperfections ...

Xuekun Guo, Juncong Lin, Kai Xu, Siddhartha Chaudhuri and Xiaogang Jin, "CustomCut: On-demand Extraction of Customized 3D Parts with 2D Sketches," Computer Graphics Forum (SGP 2016), 35(5). [PDF, 11.3M]

We present CustomCut, an on-demand part extraction algorithm. Given a sketched query, CustomCut automatically retrieves partially matching shapes from a database, identifies the region optimally matching the query in each shape, and extracts this region to produce a customized part that can be used in various modeling applications. In contrast to earlier work on sketch-based retrieval of predefined parts, our approach can extract arbitrary parts from input shapes and does not rely on a prior segmentation into semantic components ...

Hao Li, Guowei Wan, Honghua Li, Andrei Sharf, Kai Xu and Baoquan Chen, "Mobility Fitting using 4D RANSAC," Computer Graphics Forum (SGP 2016), 35(5). [PDF, 11.4M | Project page]

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions ...

Qing Yuan, Guiqing Li, Kai Xu, Xudong Chen and Hui Huang, "Space-Time Co-Segmentation of Articulated Point Cloud Sequences," Computer Graphics Forum (Eurographics 2016), 35(2). [PDF, 31M | Project page]

Consistent segmentation is to the center of many applications based on dynamic geometric data. Directly segmenting a raw 3D point cloud sequence is a challenging task due to the low data quality and large inter-frame variation across the whole sequence. We propose a local-to-global approach to co-segment point cloud sequences of articulated objects into near-rigid moving parts. Our method starts from a per-frame point clustering, derived from a robust voting-based trajectory analysis. The local segments are then progressively propagated to the neighboring frames with a cut propagation operation, and further merged through all frames using a novel space-time segment grouping tech ...

Yifei Shi, Pinxin Long, Kai Xu*, Hui Huang and Yueshan Xiong, "Data-Driven Contextual Modeling for 3D Scene Understanding," Computers and Graphics, 55: 55-67. [PDF, 4.9M]

The recent development of fast depth map fusion technique enables the realtime, detailed scene reconstruction, making the indoor scene understanding more possible than ever. To address the specific challenges in object analysis at subscene level, we propose a data-driven approach to modeling contextual information covering both intra-object part relations and inter-object object layouts. Our method combines the detection of individual objects and object groups within the same framework, enabling contextual analysis without knowing the objects in the scene a priori ...

Bo Wu, Kai Xu*, Yang Zhou, Yueshan Xiong, Hui Huang, "Skeleton-guided 3D shape distance field metamorphosis," Graphical Models, 85: 37-45. [PDF, 15M | Project page]

We introduce an automatic 3D shape morphing method without the need of manually placed anchor correspondence points. Given a source and a target shape, our approach extracts their skeletons and computes the meaningful anchor points based on their skeleton node correspondences. Based on the anchors, dense correspondences between the interior of source and target shape can be established using earth movers distance (EMD) optimization. Skeleton node correspondence, estimated with a voting-based method, leads to part correspondence which can be used to confine the dense correspondence within matched part pairs, providing smooth and plausible morphing ...

Yueqing Wang, Zhige Xie, Kai Xu, Yong Dou and Yuanwu Lei, "Convolutional Auto-Encoder Extreme Learning Machine Network for 3D Feature Learning," Neurocomputing, 174: 988-998. [PDF, 2.7M]

We propose a rapid 3D feature learning method, namely, a convolutional auto-encoder extreme learning machine (CAE-ELM) that combines the advantages of the convolutional neuron network, auto-encoder, and extreme learning machine (ELM). This method performs better and faster than other methods. In addition, we define a novel architecture based on CAE-ELM. The architecture accepts two types of 3D shape representation, namely, voxel data and signed distance field data (SDF), as inputs to extract the global and local features of 3D shapes ...


Kai Xu, Hui Huang, Yifei Shi, Hao Li, Pinxin Long, Jianong Caichen, Wei Sun and Baoquan Chen, "Autoscanning for Coupled Scene Reconstruction and Proactive Object Analysis," ACM Transactions on Graphics (SIGGRAPH Asia 2015), 34(6). [PDF, 18.7M | PPT, 2.9M | Project page | Code]

Detailed scanning of indoor scenes is tedious for humans. We propose autonomous scene scanning operated by a robot to relieve humans from such laborious task. In an autonomous setting, detailed scene acquisition is inevitably coupled with scene analysis at the required level of detail. We develop a framework for object-level scene reconstruction coupled with object-centric scene analysis. As a result, the autoscanning and reconstruction will be object-aware, guided by the object analysis ...

Ibraheem Alhashim, Kai Xu, Yixin Zhuang, Junjie Cao, Patricio Simari and Hao Zhang, "Deformation-Driven Topology-Varying 3D Shape Correspondence," ACM Transactions on Graphics (SIGGRAPH Asia 2015), 34(6). [PDF | Project page | Code]

We present a deformation-driven approach to topology-varying 3D shape correspondence. In this paradigm, the best correspondence between two shapes is the one that results in a minimal-energy, possibly topology-varying, deformation that transforms one shape to conform to the other while respecting the correspondence. Our deformation model, called GeoTopo transform, allows both geometric and topological operations such as part split, duplication, and merging, leading to fine-grained and piecewise continuous correspondence results. The key ingredient of our correspondence scheme is a deformation energy that penalizes geometric distortion, encourages structure preservation, and ...

Kai Xu, Vladimir G. Kim, Qixing Huang, Evangelos Kalogerakis, "Data-Driven Shape Analysis and Processing," Computer Graphics Forum, accepted. [PDF, 12.5M | Wikipage]

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. We provide an overview of the main concepts and components of these techniques, and discuss their application to shape classification, segmentation, matching, ...

Zhige Xie, Kai Xu*, Wen Shan, Ligang Liu, Yueshan Xiong and Hui Huang, "Projective Feature Learning for 3D Shapes with Multi-View Depth Images," Computer Graphics Forum (Pacific Graphics 2015), to appear. [PDF, 7M | Project page | Code]

Feature learning for 3D shapes is challenging due to the lack of natural paramterization for 3D surface models. We adopt the multi-view depth image representation and propose Multi-View Deep Extreme Learning Machine (MVD-ELM) to achieve fast and quality projective feature learning for 3D shapes. In contrast to existing multiview learning approaches, our method ensures the feature maps learned for different views are mutually dependent via shared weights and in each layer, their unprojections together form a valid 3D reconstruction of the input 3D shape through using normalized convolution kernels. These lead to a more accurate 3D feature learning as shown by the encouraging results in ...

Qian Zheng, Zhuming Hao, Hui Huang, Kai Xu, Hao Zhang, Daniel Cohen-Or and Baoquan Chen, "Skeleton-Intrinsic Symmetrization of Shapes," Computer Graphics Forum (Special Issue of Eurographics 2015), 37(4). [PDF, 49M | Project page]

Enhancing the self-symmetry of a shape is of fundamental aesthetic virtue. In this paper, we are interested in recovering the aesthetics of intrinsic reflection symmetries, where an asymmetric shape is symmetrized while keeping its general pose and perceived dynamics. The key challenge to intrinsic symmetrization is that the input shape has only approximate reflection symmetries, possibly far from perfect. The main premise of our work is that curve skeletons provide a concise and effective shape abstraction for analyzing approximate intrinsic symmetries as well as symmetrization. By measuring intrinsic distances over a curve skeleton for symmetry analysis, symmetrizing the skeleton, and ...


Kai Xu, Rui Ma, Hao Zhang, Chenyang Zhu, Ariel ShamirDaniel Cohen-Or and Hui Huang, "Organizing Heterogeneous Scene Collections through Contextual Focal Points," ACM Transactions on Graphics (SIGGRAPH 2014), 33(4). [PDF, 13M | Project page | Code]

We introduce focal points for characterizing, comparing, and organizing collections of complex and heterogeneous data and apply the concepts and algorithms developed to collections of 3D indoor scenes. We represent each scene by a graph of its constituent objects and define focal points as representative substructures in a scene collection. To organize a heterogeneous scene collection, we cluster the scenes based on a set of extracted focal points: scenes in a cluster are closely connected when viewed from the perspective of the representative focal points of that cluster ...

Ibraheem Alhashim, Honghua Li, Kai Xu, Junjie Cao, Rui Ma and Hao Zhang, "Topology-Varying 3D Shape Creation via Structural Blending," ACM Transactions on Graphics (SIGGRAPH 2014), 33(4). [PDF, 16.0M | Project page | Code]

We introduce an algorithm for generating novel 3D models via topology-varying shape blending. Given two shapes with different topology, our method blends them topologically and geometrically, producing continuous series of in-betweens representing new creations. The blending operations are defined on a shape representation that is structure-oriented and part-aware. Specifically, we represent a 3D shape using a spatio-structural graph composed of medial curves and sheets, which facilitate the modeling of topological variations. Fundamental topological operations including split and merge are realized by allowing one-to-many or many-to-one correspondences between the source and the target ...

Zhige Xie, Kai Xu*, Ligang Liu and Yueshan Xiong, "3D Shape Segmentation and Labeling via Extreme Learning Machine," Computer Graphics Forum (SGP 2014). [PDF, 3.3M | Code]

We propose a fast method for 3D shape segmentation and labeling via Extreme Learning Machine (ELM). Given a set of example shapes with labeled segmentation, we train an ELM classifier and use it to produce initial segmentation for test shapes. Based on the initial segmentation, we compute the final smooth segmentation through a graph-cut labeling constrained by the super-face boundaries obtained by over-segmentation and the active contours computed from ELM segmentation. Results show that our method achieves comparable results against the state-of-the-arts, but reduces the training time by approximately two orders of magnitude, both for face-level and super-face-level, making it scale well for large datasets ... we demonstrate the application of our method for online sequential learning for 3D shape segmentation ...

Xuekun Guo, Juncong Lin, Kai Xu and Xiaogang Jin, "Creature Grammar for Creative Modeling of 3D Monsters," Graphical Models (GMP 2014). [PDF, 8.1M]

Monsters and strange creatures are frequently demanded in 3D games and movies. Modeling such kind of objects calls for creativity and imagination. Especially in a scenario where a large number of monsters with various shapes and styles are required, the designing and modeling process becomes even more challenging. We present a system to assist artists in the creative design of a large collection of various 3D monsters. Starting with a small set of shapes manually selected from different categories, our system iteratively generates sets of monster models serving as the artist鈥檚 reference and inspiration. The key component of our system is a so-called creature grammar, which is a shape grammar tailored for ...

Zhige Xie, Yueshan Xiong, Kai Xu*, "AB3D: Action-Based 3D Descriptor for Shape Analysis," The Visual Computer Journal (CGI 2014). [PDF, 3.7M | Erratum]

Existing 3D models often exhibit both large intra-class and inter-class variations in shape geometry and topology, making the consistent analysis of functionality challenging. Traditional 3D shape analysis methods which rely on geometric shape descriptors can not obtain satisfying results on these 3D models. We develop a new 3D shape descriptor based on the interactions between 3D models and virtual human actions, which is called Action-Based 3D Descriptor (AB3D). Due to the implied semantic meanings of virtual human actions, we obtain encouraging results on consistent segmentation based on AB3D. Finally, we present a method for recognition and reconstruction of scanned 3D indoor scenes using our AB3D ...

Jun Li, Weiwei Xu, Zhiquan Cheng, Kai Xu*, and Reinhard Klein, "Lightweight Wrinkle Synthesis for 3D Facial Modeling and Animation," Computer-Aided Design (SPM 2014). [PDF, 3.9M].

We present a lightweight non-parametric method to generate wrinkles for 3D facial modeling and animation. The key lightweight feature of the method is that it can generate plausible wrinkles using a single low-cost Kinect camera and one high quality 3D face model with details as the example. Our method works in two stages: (1) Offline personalized wrinkled blendshape construction ... (2) Online 3D facial performance capturing ...

Kai Lu, Yi Zhang, Kai Xu, Yinghui Gao and Richard Wilson, "Approximate Maximum Common Sub-graph Isomorphism Based on Discrete-Time Quantum Walk," ICPR 2014. [PDF, 650K]

Maximum common sub-graph isomorphism (MCS) is a famous NP-hard problem in graph processing. The problem has found application in many areas where the similarity of graphs is important, for example in scene matching, video indexing, chemical similarity and shape analysis. In this paper, a novel algorithm Qwalk is proposed for approximate MCS, utilizing the discrete-time quantum walk. Based on the new observation that isomorphic neighborhood group matches can be detected quickly and conveniently by the destructive interference of a quantum walk, the new algorithm locates an approximate solution via ...

Yin Chen, Gang Dang, Zhiquan Cheng and Kai Xu*, "Fast capture of personalized avatar using two Kinects,"Journal of Manufacturing Systems, 33(1):233-240. [PDF, 2.9M]

We present a system for fast capture of personalized 3D avatar using two Kinects. The key feature of the system is that the capturing process can be finished in a moment, or quantitatively 3 s, which is short enough for the person being captured to hold a static pose stably and comfortably. This fast capture is achieved by using two calibrated Kinects to capture the front and back side of the person simultaneously. To alleviate the view angle limit, the two Kinects are driven by their automatic motors to capture three scans covering the upper, middle and lower part of the person from front and back respectively, resulting in three partial scans for each Kinect. After denoising, all partial scans are rigidly aligned together ...


Jun Wang, Kai Xu, Ligang Liu, Junjie Cao, Shengjun Liu, Zeyun Yu, and Xianfeng Gu, "Consolidation of Low-quality Point Clouds from Outdoor Scenes," Computer Graphics Forum (SGP 2013). [PDF, 30M]

The emergence of laser/LiDAR sensors, reliable multi-view stereo techniques and more recently consumer depth cameras have brought point clouds to the forefront as a data format useful for a number of applications. Unfortunately, the point data from those channels often incur imperfection, frequently contaminated with severe outliers and noise. This paper presents a robust consolidation algorithm for low-quality point data from outdoor scenes, which essentially consists of two steps: 1) outliers filtering and 2) noise smoothing. We first design a connectivity based scheme to evaluate outlierness and thereby detect sparse outliers. Meanwhile, a clustering method is used to further remove small dense outliers. Both outlier removal methods are insensitive to the choice of the neighborhood size and the levels of outliers. Subsequently, we propose a novel approach to estimate normals for noisy points based on robust partial rankings, which is the basis of noise smoothing ...

Xiaohua Xie, Kai Xu, Niloy Mitra, Daniel Cohen-Or, Wenyong Gong, Qi Su and Baoquan Chen, "Sketch-to-Design: Context-based Part Assembly," Computer Graphics Forum, 32(8): 233-245. [PDF, 9M | Project page]

Designing 3D objects from scratch is difficult, especially when the user intent is fuzzy without a clear target form. In the spirit of modeling-by-example, we facilitate design by providing reference and inspiration from existing model contexts. We rethink model design as navigating through different possible combinations of part assemblies based on a large collection of pre-segmented 3D models.We propose an interactive sketch-to-design system, where the user sketches prominent features of parts to combine. The sketched strokes are analyzed individually and in context with the other parts to generate relevant shape suggestions via a design gallery interface ...

Hao Zhang, Kai Xu*, Wei Jiang, Jinjie Lin, Daniel Cohen-Or and Baoquan Chen, "Layered Analysis of Irregular Facades via Symmetry Maximization," ACM Transactions on Graphics (SIGGRAPH 2013), 32(4). [PDF, 33M | MOV. 70M | Project page | Code | Data]

We present an algorithm for hierarchical and layered analysis of irregular facades, seeking a high-level understanding of facade structures. By introducing layering into the analysis, we no longer view a facade as a flat structure, but allow it to be structurally separated into depth layers, enabling more compact and natural interpretations of building facades. Computationally, we perform a symmetry-driven search for an optimal hierarchical decomposition defined by split and layering operations applied to an input facade. The objective is symmetry maximization ...

Oliver van Kaick, Kai Xu, Hao Zhang, Yanzhen Wang, Shuyang Sun, Ariel Shamir and Daniel Cohen-Or, "Co-Hierarchical Analysis of Shape Structures," ACM Transactions on Graphics (SIGGRAPH 2013), 32(4). [PDF, 17M | Project page]

We introduce an unsupervised co-hierarchical analysis of a set of shapes, aimed at discovering their hierarchical part structures and revealing relations between geometrically dissimilar yet functionally equivalent shape parts across the set. The central problem is that of representative co-selection. For each shape in the input set, one representative hierarchy (tree) is selected from among many possible interpretations of the hierarchical structure of the shape. Collectively, the selected tree representatives maximize the structural similarity among them ...

Wei Jiang, Kai Xu*Zhiquan Cheng, and Hao Zhang, "Skeleton-Based Intrinsic Symmetry Detection on Point Clouds," Graphical Models, 75(4):177-188. [PDF, 5.6M]

We present a skeleton-based algorithm for intrinsic symmetry detection on imperfect 3D point cloud data. The data imperfections such as noise and incompleteness make it difficult to reliably compute geodesic distances, which play essential roles in existing intrinsic symmetry detection algorithms. In this paper, we leverage recent advances in curve skeleton extraction from point clouds for symmetry detection. ... Starting from a curve skeleton extracted from an input point cloud, we first compute symmetry electors, each of which is composed of a set of skeleton node pairs pruned with a cascade of symmetry filters ... Experiments on raw point clouds, captured by a 3D scanner or the Microsoft Kinect, demonstrate the robustness of our algorithm. We also apply our method to repair incomplete scans based on the detected intrinsic symmetries.

Wei Jiang, Kai Xu*, Zhiquan Cheng, Ralph Martin, and Gang Dang, "Curve Skeleton Extraction by Coupled Graph Contraction and Surface Clustering," Graphical Models, 75(3): 137-148. (A previous version appeared at CVM 2012) [PDF, 2.4M]

In this paper, we present a practical algorithm to extract a curve skeleton of a 3D shape. The core of our algorithm comprises coupled processes of graph contraction and surface clustering. Given a 3D shape represented by a triangular mesh, we first construct an initial skeleton graph by directly copying the connectivity and geometry information from the input mesh. Graph contraction and surface clustering are then performed iteratively. The former merges certain graph nodes based on computation of an approximate centroidal Voronoi diagram, seeded by subsampling the graph nodes from the previous iteration. Meanwhile, a coupled surface clustering process serves to regularize the graph contraction ... It can also handle point cloud data if we first build an initial skeleton graph based on k-nearest neighbors ...


Kai Xu, Hao Zhang, Wei Jiang, Ramsay Dyer, Zhiquan Cheng, Ligang Liu, and Baoquan Chen, "Multi-Scale Partial Intrinsic Symmetry Detection," ACM Transactions on Graphics (SIGGRAPH Asia 2012), 31(6). [PDF, 15.6MPPTX, 16.0M | Project page | Data]

We present an algorithm for multi-scale partial intrinsic symmetry detection over 2D and 3D shapes, where the scale of a symmetric region is defined by intrinsic distances between symmetric points over the region. To identify prominent symmetric regions which overlap and vary in form and scale, we decouple scale extraction and symmetry extraction by performing two levels of clustering. First, significant symmetry scales are identified by clustering sample point pairs from an input shape. Since different point pairs can share a common point, shape regions covered by points in different scale ...

Kai Xu, Hao Zhang, Daniel Cohen-Or, and Baoquan Chen, "Fit and Diverse: Set Evolution for Inspiring 3D Shape Galleries," ACM Transactions on Graphics (SIGGRAPH 2012), 31(4). [PDF, 15.8M | MOV, 51.7M | PPTX, 22.9M | Project page | Data]

We introduce set evolution as a means for creative 3D shape modeling, where an initial population of 3D models is evolved to produce generations of novel shapes. Part of the evolving set is presented to a user as a shape gallery to offer modeling suggestions. User preferences define the fitness for the evolution so that over time, the shape population will mainly consist of individuals with good fitness. However, to inspire the user's creativity, we must also keep the evolving set diverse. Hence the evolution is "fit and diverse", drawing motivation from evolution theory. We introduce a novel part crossover operator which works at the finer-level part structures of the shapes ...

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Yanzhen Wang, Yueshan Xiong, Kai Xu, and Dong Liu, "vKASS: A Surgical Procedure Simulation System for Arthroscopic Anterior Cruciate Ligament Reconstruction" Computer Animation and Virtual World. 24(1): 25-41. [PDF, 2.2M]

Arthroscopic surgeries, which are widely used for anterior cruciate ligament (ACL) reconstruction, not only require advanced hand鈥揺ye coordination but also involve complicated surgical procedure, necessitating simulation-based training for surgeons. This paper describes a surgical procedure simulation system for the training of arthroscopic ACL reconstruction. Different from existing simulation-based training systems for basic surgical skills, this system provides a complete simulation for the entire procedure of arthroscopic ACL reconstruction, involving operations such as puncturing, probing, incision, and drilling. In this system, we employ a linear elastic finite element method and position-based dynamics for deformable modeling ...


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Kai Xu, Hanlin Zheng, Hao Zhang, Daniel Cohen-Or, Ligang Liu, and Yueshan Xiong, "Photo-Inspired Model-Driven 3D Object Modeling," ACM Transactions on Graphics (SIGGRAPH 2011), 30(4). [PDF, 12.6M | MOV, 33.9M | PPTX, 14.3M | Project page]

We introduce an algorithm for 3D object modeling where the user draws creative inspiration from an object captured in a single photograph. Our method leverages the rich source of photographs for creative 3D modeling. However, with only a photo as a guide, creating a 3D model from scratch is a daunting task. We support the modeling process by utilizing an available set of 3D candidate models. Specifically, the user creates a digital 3D model as a geometric variation from a 3D candidate. Our modeling technique consists of two major steps. The first step is a user-guided image-space object segmentation to reveal the structure of the photographed object. The core step is the second one, in which a 3D candidate is automatically deformed to fit the photographed target ...

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Yanzhen Wang, Kai Xu, Jun Li, Hao Zhang, Ariel Shamir, Ligang Liu, Zhi-Quan Cheng, and Yueshan Xiong, "Symmetry Hierarchy of Man-Made Objects," Computer Graphics Forum (Special Issue of Eurographics 2011), 30(2): 287-296. [PDF, 12M | MOV, 28M | Project page]

We introduce symmetry hierarchy of man-made objects, a high-level structural representation of a 3D model providing a symmetry-induced, hierarchical organization of the model's constituent parts. We show that symmetry hierarchy naturally implies a hierarchical segmentation that is more meaningful than those produced by local geometric considerations. We also develop an application of symmetry hierarchies for structural shape editing.


Kai Xu, Honghua Li, Hao Zhang, Daniel Cohen-Or, Yueshan Xiong, and Zhi-Quan Cheng, "Style-Content Separation by Anisotropic Part Scales," ACM Transactions on Graphics (SIGGRAPH Aisa 2010), 29(5). [PDF, 9.8M | Project page]

We perform co-analysis of a set of man-made 3D objects to allow the creation of novel instances derived from the set. We analyze the objects at the part level and treat the anisotropic part scales as a shape style. The co-analysis then allows style transfer to synthesize new objects. The key to co-analysis is part correspondence, where a major challenge is the handling of large style variations and diverse geometric content in the shape set. We propose style-content separation as a means to address this challenge. Specifically, we define a correspondence-free style signature for style clustering. We show that confining analysis to within a style cluster facilitates tasks such as ... 

Z.-Q. Cheng, W. Jiang, G. Dang, R. Martin, J. Li, H. Li, Y. Chen, Y. Wang, B. Li, K. Xu, S. Jin, "Non-rigid Registration in 3D Implicit Vector Space," In: Proc. of Shape Modeling International 2010, Aix-en-Provence, France, 2010. [PDF, 4.3M]

We present an implicit approach for pair-wise non-rigid registration of moving and deforming objects. Shapes of interest are implicitly embedded in the 3D implicit vector space. In this implicit embedding space, registration is performed using a global-to-local framework. Firstly, a non-linear optimization functional defined on the vector distance function is used to find the global alignment between shapes. Secondly, an incremental cubic B-spline free form deformation is used to recover the non-rigid transformation parameters ...


Kai Xu, Hao Zhang, Andrea Tagliasacchi, Ligang Liu, Guo Li, Min Meng, and Yueshan Xiong, "Partial Intrinsic Reflectional Symmetry of 3D Shapes," ACM Transactions on Graphics (SIGGRAPH Aisa 2009), 28(5). [PDF, 15M | Video, 37M | Project page]

While many 3D objects around us exhibit various forms of global symmetries, prominent intrinsic symmetries which exist only on parts of an object are also well recognized. Such partial symmetries are often seen as more natural compared to a global one, especially on a composite shape. In this paper, we introduce algorithms to extract and utilize partial intrinsic reflectional symmetries (PIRS) of a 3D shape. Given a closed 2-manifold mesh, we develop a voting scheme to obtain an intrinsic reflectional symmetry axis (IRSA) transform ...

Kai Xu, Daniel Cohen-Or, Tao Ju, Ligang Liu, Hao Zhang, Shizhe Zhou, and Yueshan Xiong, "Feature-Aligned Shape Texturing," ACM Transactions on Graphics (SIGGRAPH Aisa 2009), 28(5). [PDF, 20.1M | Video, 31M | Project page | Code]

We present an implicit approach for pair-wise non-rigid registration of moving and deforming objects. Shapes of interest are implicitly embedded in the 3D implicit vector space. In this implicit embedding space, registration is performed using a global-to-local framework. Firstly, a non-linear optimization functional defined on the vector distance function is used to find the global alignment between shapes. Secondly, an incremental cubic B-spline free form deformation is used to recover the non-rigid transformation parameters ...

Kai Xu, Hao Zhang, Daniel Cohen-Or, and Yueshan Xiong, "Dynamic Harmonic Fields for Surface Processing," Computers and Graphics (Special Issue of Shape Modeling International 2009), 33(3): 391-398. [PDF, 0.6M | Video, 49.2M | Source code]

We propose a method for fast updating of harmonic fields defined on polygonal meshes, enabling real-time insertion and deletion of constraints. Our approach utilizes the penalty method to enforce constraints in harmonic field computation. It maintains the symmetry of the Laplacian system and takes advantage of fast multi-rank updating and downdating of Cholesky factorization, achieving both speed and numerical stability. We demonstrate how the interactivity induced by fast harmonic field update can be utilized in several applications ...

Kai Xu, Zhi-Quan Cheng, Yanzhen Wang, Yueshan Xiong, and Hao Zhang, "Quality Encoding for Tetrahedral Mesh Optimization," Computers and Graphics (Special Issue of Shape Modeling International 2009), 33(3): 250-261. [PDF, 1M]

We define quality differential coordinates (QDC) for per-vertex encoding of the quality of a tetrahedral mesh. QDC measures the deviation of a mesh vertex from a position which maximizes the combined quality of the tetrahedra incident at that vertex. Our formulation allows the incorporation of element quality metrics into QDC construction to penalize badly shaped and inverted tetrahedra. We develop an algorithm for tetrahedral mesh optimization through energy minimization driven by QDC ...


Yanzhen Wang, Kai Xu, Yueshan Xiong, and Zhi-Quan Cheng, "2D Shape Deformation Based on As-Rigid-As-Possible Squares Matching," Computer Animation and Virtual World (Special Issue of CASA 2008), 19(3-4): 411-420. [PDF, 5.8M]

In this paper, we propose a fast and stable method for 2D shape deformation based on rigid square matching. Our method utilizes uniform quadrangular control meshes for 2D shapes and tries to maintain the rigidity of each square in the control mesh during user mani-pulation. A rigid shape matching method is performed to find an optimal pure rotational transformation for each square in the control mesh. An iterative solver is proposed to com-pute the final deformation result for the entire control mesh by minimizing the difference between ...

Kai Xu, Yanzhen Wang, Yueshan Xiong, and Zhi-Quan Cheng, "Interactive Shape Manipulation Based on Space Deformation with Harmonic-Guided Clustering," In: Proc. of International Conference on Computer Animation and Social Agent, 2008. [PDF, 0.3M]

We present an efficient and effective deformation algorithm for interactive shape manipulation. To obtain the advantages of both surface and space-based deformation, we propose to maximally incorporate surface geometry information into space deformation framework while preventing the dependence on surface representation. Our deformation model significantly reduces the problem size through sampling the shape surface and ...

Zhi-Quan Cheng, Yanzhen Wang, Bao Li, Kai Xu, Gang Dang, and Shiyao Jin, "A Survey of Methods for Moving Least Squares Surfaces," In: Proc. of IEEE/Eurographics Symposium on Point Based Graphics 2008, Los Angeles, USA, 2008. [PDF, 2.2M]

Moving least squares (MLS) surfaces representation directly defines smooth surfaces from point cloud data, on which the differential geometric properties of point set can be conveniently estimated. Nowadays, the MLS surfaces have been widely applied in the processing and rendering of point-sampled models and increasingly adopted as the standard definition of point set surfaces. We classify the MLS surface algorithms into two types: projection MLS surfaces and implicit MLS surfaces, according to employing a stationary projection or a scalar field in their definitions ...


Zhi-Quan Cheng, Kai Xu, Bao Li, Yanzhen Wang, Shi-Yao Jin, and Gang Dang, "A Mesh Meaningful Segmentation Algorithm Using Skeleton and Minima-Rule," In: Proceedings of International Symposium on Visual Computing 2007, Lake Tahoe, USA, 2007. [PDF, 3.3MB]

In this paper, a hierarchical shape decomposition algorithm is proposed, which integrates the advantages of skeleton-based and minima-rule based meaningful segmentation algorithms. The method makes use of new geometrical and topological functions of skeleton to define initial cutting critical points, and then employs salient contours with negative minimal principal curvature values to determine natural final boundary curves among parts ...


Kai Xu, Yueshan Xiong, Yanzhen Wang, Ke Tan, and Guangyou Guo, "A Simple and Stable Feature-Preserving Smoothing Method for Contours-Based Reconstructed Meshes," In: Proceedings of ACM GRAPHITE 2006, Kuala Lumpur, 2006.

In this paper, we develop a new feature preserving smoothing method for the irregular and coarse meshes reconstructed from 2D contours. To make the feature detecting robust, a new detecting algorithm using the continuity among adjacent contours is proposed. Then the original mesh is subdivided adaptively according to the detected geometric features and smoothed with isotropic method. With the help of that, our algorithm obtains not only the feature-preserving result ...

Yanzhen Wang, Yueshan Xiong, Kai Xu, Ke Tan, and Guangyou Guo, "A Mass-spring Model for Surface Mesh Deformation Based on Shape Matching," In: Proceedings of ACM GRAPHITE 2006, Kuala Lumpur, 2006.

In this paper, we propose a mass-spring model based on shape matching for real-time deformable modeling in virtual reality systems. By defining a rigid core for surface mesh model and adding a new generalized spring for each mass, our surface mesh model can preserve its original geometric features such as volume and shape. Then, we use shape matching approaches to update the rigid core of the model dynamically so as to simulate global deformations. At last, we adopt an inverse dynamics technique to deal with the resulting deformations ...