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检索条件"机构=State Key Lab. of CAD & Computer Graphics"

共 120 条记录，以下是51-60 订阅

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Point sampled surface reconstruction based on local geometry

引用

2nd International Conference on Edutainment, Edutainment 2007

作者： Lanfang, Miao Qunsheng, Peng Department of Computer Science Zhejiang Normal University Jinhua 321004 China State Key Lab. of CAD and CG Zhejiang Univerisity Hangzhou 310027 China

ISBN: (纸本)9783540730101

In this paper, we presented a point sampled surface reconstruction method based on local geometry. First, an adaptive Binary Space Partition (aBSP) tree was built based on the local shape complexity which was judged by three factors: local main curvature, the normal cone and the number of points. Different local complexities produce different aBSP-trees. Then, each leaf node in the aBSP tree was approximated by a weighted quadric function and the center points set of aBSP tree's leaf nodes could be treated as one approximation to the original point set at a given complexity of the local shape. Finally, a ray tracer based on point was used to render these aBSP-trees, which avoids triangulating of implicit surfaces before they are rendered. The experimental results show that the method can reconstruct sharp features very conveniently and effectively. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Surface reconstruction

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Unsupervised face-name association via commute distance

Unsupervised face-name association via commute distance

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20th ACM International Conference on Multimedia, MM 2012

作者： Bu, Jiajun Xu, Bin Wu, Chenxia Chen, Chun Zhu, Jianke Cai, Deng He, Xiaofei Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Zhejiang University Hangzhou China State Key Lab. of CAD and CG College of Computer Science Zhejiang University Hangzhou China

ISBN: (纸本)9781450310895

Recently, the task of unsupervised face-name association has received a considerable interests in multimedia and information retrieval communities. It is quite different with the generic facial image annotation problem because of its unsupervised and ambiguous assignment properties. Specifically, the task of face-name association should obey the following three constraints: (1) a face can only be assigned to a name appearing in its associated caption or to null;(2) a name can be assigned to at most one face;and (3) a face can be assigned to at most one name. Many conventional methods have been proposed to tackle this task while suffering from some common problems, eg, many of them are computational expensive and hard to make the null assignment decision. In this paper, we design a novel framework named face-name association via commute distance (FACD), which judges face-name and face-null assignments under a unified framework via commute distance (CD) algorithm. Then, to further speed up the on-line processing, we propose a novel anchor-based commute distance (ACD) algorithm whose main idea is using the anchor point representation structure to accelerate the eigen-decomposition of the adjacency matrix of a graph. Systematic experiment results on a large scale and real world image-caption database with a total of 194,046 detected faces and 244,725 names show that our proposed approach outperforms many state-of-the-art methods in performance. Our framework is appropriate for a large scale and real-time system. © 2012 ACM.

关键词： Real time systems

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Parallel field ranking 12

Parallel field ranking

引用

18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012

作者： Ji, Ming Lin, Binbin He, Xiaofei Cai, Deng Han, Jiawei Department of Computer Science University of Illinois at Urbana-Champaign Urbana IL United States State Key Lab. of CAD and CG College of Computer Science Zhejiang University China

ISBN: (纸本)9781450314626

Recently, ranking data with respect to the intrinsic geometric structure (manifold ranking) has received considerable attentions, with encouraging performance in many applications in pattern recognition, information retrieval and recommendation systems. Most of the existing manifold ranking methods focus on learning a ranking function that varies smoothly along the data manifold. However, beyond smoothness, a desirable ranking function should vary monotonically along the geodesics of the data manifold, such that the ranking order along the geodesics is preserved. In this paper, we aim to learn a ranking function that varies linearly and therefore monotonically along the geodesics of the data manifold. Recent theoretical work shows that the gradient field of a linear function on the manifold has to be a parallel vector field. Therefore, we propose a novel ranking algorithm on the data manifolds, called Parallel Field Ranking. Specifically, we try to learn a ranking function and a vector field simultaneously. We require the vector field to be close to the gradient field of the ranking function, and the vector field to be as parallel as possible. Moreover, we require the value of the ranking function at the query point to be the highest, and then decrease linearly along the manifold. Experimental results on both synthetic data and real data demonstrate the effectiveness of our proposed algorithm. © 2012 ACM.

关键词： Recommender systems

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An exploration of improving collab.rative recommender systems via user-item subgroups 12

An exploration of improving collaborative recommender system...

引用

21st Annual Conference on World Wide Web, WWW'12

作者： Xu, Bin Bu, Jiajun Chen, Chun Cai, Deng Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Zhejiang University Hangzhou China State Key Lab. of CAD and CG College of Computer Science Zhejiang University Hangzhou China

ISBN: (纸本)9781450312295

Collab.rative filtering (CF) is one of the most successful recommendation approaches. It typically associates a user with a group of like-minded users based on their preferences over all the items, and recommends to the user those items enjoyed by others in the group. However we find that two users with similar tastes on one item subset may have totally different tastes on another set. In other words, there exist many user-item subgroups each consisting of a subset of items and a group of like-minded users on these items. It is more natural to make preference predictions for a user via the correlated subgroups than the entire user-item matrix. In this paper, to find meaningful subgroups, we formulate the Multiclass Co-Clustering (MCoC) problem and propose an effective solution to it. Then we propose an unified framework to extend the traditional CF algorithms by utilizing the subgroups information for improving their top-N recommendation performance. Our approach can be seen as an extension of traditional clustering CF models. Systematic experiments on three real world data sets have demonstrated the effectiveness of our proposed approach.

关键词： Collab.rative filtering

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Generating time lines with virtual words for time-varying data visualization 12

Generating time lines with virtual words for time-varying da...

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5th International Symposium on Visual Information Communication and Interaction, VINCI 2012

作者： Yu, Li Lu, Aidong Chen, Wei Dept. of Computer Science UNC Charlotte Charlotte NC United States State Key Lab. of CAD and CG Zhejiang University Hangzhou Zhejiang China

ISBN: (纸本)9781450317825

This paper presents a time line visualization approach, which allows users to study temporal relationships through encoding their interested data properties to time lines with different shapes and locations. Specifically, our approach extracts key data features as virtual words and uses them to encode various data properties. The distributions of virtual words across time are further applied to study various temporal relationships by generating time lines, which renders sampled time steps as points and temporal sequence as a line. Our approach consists of the three following components. First, we select feature points and collect feature descriptors to build a space of data properties, where virtual words are extracted as representative vectors. Second, the virtual words are applied to characterize feature points and their distribution statistics are used to measure temporal relationships. Third, we present several case studies to visualize time lines for different data visualization and analysis purposes. Our time line visualization can be used for both summarization and exploration of overall temporal relationships. We demonstrate with examples that time lines can serve as effective exploration, comparison, and visualization tools to study time-varying datasets. © 2012 ACM.

关键词： Visualization

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K-way min-max cut for image clustering and junk images filtering from Google images

K-way min-max cut for image clustering and junk images filte...

引用

18th ACM International Conference on Multimedia ACM Multimedia 2010, MM'10

作者： Xie, Feng Shen, Yi He, Xiaofei State Key Lab. of CAD and CG College of Computer Science Zhejiang University Hangzhou China Dept. of Computer Science UNC-Charlotte Charlotte NC 28223 United States

ISBN: (纸本)9781605589336

Currently most existing image search engines such as Google Images index web images majorly using text keywords extracted from the context, which may return large amount of junk information. We propose a novel clustering based filtering method to filter those junk images. Firstly we apply K-way min-max cut to cluster images returned by Google into multiple clusters based on the mixture of feature kernels, with kernel weights being determined automatically instead of hard fix. Secondly we select the best cluster in a robust way, and rank all the rest clusters according to their similarity with the best one. Finally those low-rank clusters can be filtered out as junk clusters. In experiments we obtain very comparative filtering performance to the current state-of-the-art, and improve Google Images search results significantly. © 2010 ACM.

关键词： Mixtures

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Using emotion transmission to simulate spectator behaviors

Using emotion transmission to simulate spectator behaviors

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11th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry, VRCAI 2012

作者： Xiang, Nan Pan, Zhigeng Zhang, Mingmin State Key Lab. of CAD and CG Zhejiang Universiy China Digital Media and Human-Computer Interaction Research Center Hangzhou Normal University Hangzhou China

ISBN: (纸本)9781450318259

In this paper, we introduced a novel method to simulate moving spectator crowd behaviours. Different from the common methods, we taken the emotional affections between spectators into consideration and calculated these affections by heat conduction model. The generation loops can be divided into three steps. We firstly exploited PAD space to build spectators' emotional states. Then we updated spectators' positions and generated their emotional affections by emotion transmission equations which were formulated from heat conduction equations. We called this step dynamic emotion transmission. At last, we mapped their emotions to actions. Using this algorithm, we can simulate more realistic crowd behaviours. © 2012 ACM.

关键词： Heat conduction

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Image-based BRDF design

Image-based BRDF design

引用

2019 Material Appearance Conference, MAAP 2019

作者： Davis, Ezra Shi, Weiqi Rushmeier, Holly Dorsey, Julie Wu, Hongzhi Department of Computer Science Yale University New HavenCT United States State Key Lab. of CAD&CG Zhejiang University Hangzhou China

Material appearance design usually requires an unintuitive selection of parameters for an analytical BRDF (bidirectional reflectance distribution functions) formula or time consuming acquisition of a BRDF table from a physical material sample. We propose a material design system that can take visual input in the form of images of an object with known geometry and lighting and produce a plausible BRDF table within a class of BRDFs. We use the principal components of a large dataset of BRDFs to reconstruct a full BRDF table from a sparse input of BRDF values at pairs of incoming and outgoing light directions. To get visual user input, we allow the user to provide their own object and then generate guide images with selected lighting directions. Once the user shades the guide images, we construct the reflectance table and allow the user to iteratively refine the material appearance. We present preliminary results for image-based design, and discuss the open issues remaining to make the approach practical for mainstream use. © 2019, Society for Imaging Science and Technology.

关键词： Lighting

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3D fashion fast modeling from photographs

3D fashion fast modeling from photographs

引用

2009 WRI World Congress on computer Science and Information Engineering, CSIE 2009

作者： Li, Wei-Long Lu, Guo-Dong Geng, Yu-Lei Wang, Jin State Key Lab. of CAD and CG Zhejiang University Hangzhou Zhejiang310027 China Department of Computer Guangxi University of Technology Liuzhou Guangxi 545006 China

ISBN: (纸本)9780769535074

The paper presents a technique of 3D fashion modeling from photographs of wearing clothes in front and back views. Firstly, an efficient segmentation method is applied on photographs to obtain the silhouette of the fashion. Then, a template-based feature extraction algorithm is introduced to determine the feature points on the garment. Finally, a viewdependent deformation technique is described to construct the fashion by deforming the garment template. Our segmentation algorithm is derived from Mathematical Morphology and image difference method. The deformation technique is related to freeform deformations and vector field of mannequin. With our deformation method, the main feature of fashion is preserved. Compared with other predefined fashion modeling approaches, the efficient and realistic of constructing is greatly increased. The functionality of garment model constructed by our method can apply to some others applications for garment industry. © 2008 IEEE.

关键词： Mathematical morphology

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Adaptive data fitting by the progressive-iterative approximation

Adaptive data fitting by the progressive-iterative approxima...

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作者： Lin, Hongwei Institute of Computer Image and Graphics Department of Mathematics Zhejiang University Hangzhou 310058 China State Key Lab. of CADandCG Zhejiang University Hangzhou 310058 China

In this paper, we develop the adaptive data fitting algorithms by virtue of the local property of the Progressive-iterative approximation (abbr. PIA), which generates the fitting curve (patch) by adjusting the control points of a blending curve (patch) iteratively. In the adaptive data fitting algorithms, the control points are classified into two classes, namely, active and fixed control points, and only the active control points need to be adjusted in each iteration, thus saving computation greatly. Lots of examples and experimental data are presented to demonstrate the efficiency of the adaptive data fitting algorithm. Since the PIA method can be made parallel easily, the adaptive data fitting algorithm developed in this paper has important applications in parallel large scale data fitting. © 2012 Elsevier B.V.

关键词： Blending

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