Lecture Notes in Computer Science 3852Commenced Publication in 1973Founding and Former Series Editors:Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen

Editorial Board

David HutchisonLancaster University, UK

Takeo KanadeCarnegie Mellon University, Pittsburgh, PA, USA

Josef KittlerUniversity of Surrey, Guildford, UK

Jon M. KleinbergCornell University, Ithaca, NY, USA

Friedemann MatternETH Zurich, Switzerland

John C. MitchellStanford University, CA, USA

Moni NaorWeizmann Institute of Science, Rehovot, Israel

Oscar NierstraszUniversity of Bern, Switzerland

C. Pandu RanganIndian Institute of Technology, Madras, India

Bernhard SteffenUniversity of Dortmund, Germany

Madhu SudanMassachusetts Institute of Technology, MA, USA

Demetri TerzopoulosNew York University, NY, USA

Doug TygarUniversity of California, Berkeley, CA, USA

Moshe Y. VardiRice University, Houston, TX, USA

Gerhard WeikumMax-Planck Institute of Computer Science, Saarbruecken, Germany

P.J. Narayanan Shree K. NayarHeung-Yeung Shum (Eds.)

Computer Vision –ACCV 2006

7th Asian Conference on Computer VisionHyderabad, India, January 13-16, 2006Proceedings, Part II

1 3

Volume Editors

P.J. NarayananCentre for Visual Information TechnologyInternational Institute of Information TechnologyGachibowli, Hyderabad 500032, IndiaE-mail: pjn@iiit.ac.in

Shree K. NayarColumbia University, Department of Computer Science530 West 120th Street, New York, NY 10027, USAE-mail: nayar@cs.columbia.edu

Heung-Yeung ShumMicrosoft Research Asia49 Zhichun Road, Beijing 100080, ChinaE-mail: hshum@microsoft.com

Library of Congress Control Number: 2005938106

CR Subject Classification (1998): I.4, I.5, I.2.10, I.2.6, I.3.5, F.2.2

ISSN 0302-9743ISBN-10 3-540-31244-7 Springer Berlin Heidelberg New YorkISBN-13 978-3-540-31244-4 Springer Berlin Heidelberg New York

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Preface

Welcome to the 7th Asian Conference on Computer Vision. It gives us great plea-sure to bring forth its proceedings. ACCV has been making its rounds throughthe Asian landscape and came to India this year. We are proud of the technicalprogram we have put together and we hope you enjoy it.

Interest in computer vision is increasing and ACCV 2006 attracted about 500submission. The evaluation team consisted of 27 experts serving as Area Chairsand about 270 reviewers in all. The whole process was conducted electronicallyin a double-blind manner, a first for ACCV. Each paper was assigned to an AreaChair who found three competent reviewers for it. We were able to contain themaximum load on the reviewers to nine and the average load to less than six.The review form had space for qualitative and quantitative evaluation of thepaper on nine aspects. The submitted reviews underwent an elaborate process.First, they were seen by the Area Chair, who resolved divergences of opinionamong reviewers, if any. The Area Chair then wrote qualitative comments anda quantitative score along with his/her initial recommendation on the paper.These were looked at by Program Co-chairs and compiled into a probables list.The Area Chairs and Program Co-chairs met in Beijing during ICCV to discussthis list and arrived at the final list of 64 oral papers and 128 posters. Naturally,many deserving papers could not be accommodated.

Katsushi Ikeuchi has been unflinching in his support of ACCV as a wholeand ACCV 2006 in particular. His help was critical at many stages. We mustthank the Area Chairs and the reviewers for their time and effort towards theconference. From IIIT Hyderabad, C.V. Jawahar and Anoop M. Namboodiri con-tributed in many ways with the program. The enthusiastic team of students fromthe Centre for Visual Information Technology (CVIT) was behind it fully. Kar-teek Alahari, Kiran Babu Varanasi, Sumeet Gupta, Sukesh Kumar, and Satya-narayana made all the logistics of the CFP, paper submission, review process,and preparation of the proceedings really possible. The International Instituteof Information Technology was fully behind the conference as a team and de-serves our deep gratitude. Finally – but most importantly – we wish to thankthe authors who showed great enthusiasm for ACCV.

ACCV has been gaining in stature as a platform to showcase the best ofcomputer vision research over the years. We hope the 2006 edition has broughtit forward at least a little. Computer vision continues to be an exciting area andconferences like these provide the much needed light to many who will embarkon a journey down its path.

P J NarayananShree NayarHarry Shum

(Program Chairs)

Conference Committees

General ChairsNarendra Ahuja

University of Illinois & IIIT HyderabadTakeo Kanade

Carnegie Mellon UniversityTieniu Tan

Chinese Academy of Sciences

Program ChairsP.J. NarayananIIIT, Hyderabad

Shree NayarColumbia University

Harry ShumMicrosoft Research Asia

Organizing ChairsC.V. Jawahar

IIIT, HyderabadSantanu Chaudhury

IIT, Delhi

Advisory CommitteeMasahiko Yachida, Osaka University

Eam Khwang Teoh, Nanyang Technological UniversityRoland Chin, Hong Kong University of Science and Technology

Wen-Hsiang Tsai, Chiao Tang UniversityDavid Suter, Monash University

Sang-Uk Lee, Seoul National UniversityKatsushi Ikeuchi, Tokyo University

B. L. Deekshatulu, University of HyderabadD. Dutta Majumdar, Indian Statistical Institute

B. N. Chatterjee, Indian Institute of Technology, Kharagpur

Area Chairs

Yaron Caspi Hebrew UniversityTat Jen Cham Nanyang Technological UniversityBhabatosh Chanda Indian Statistical InstituteSubhasis Chaudhuri Indian Institute of Technology, MumbaiYi-ping Hung National Taiwan UniversityPrem Kalra Indian Institute of Technology, DelhiChandra Kambhamettu University of DelawareMohan Kankanahalli National University of SingaporeIn So Kweon Korean Advanced Institute of Science and TechnologySang Wook Lee Sogang UniversityRavikanth Malladi GE John Welch Technology CentreHiroshi Murase Nagoya UniversityTomas Pajdla Czech Technical UniversityLong Quan Hong Kong University of Science and TechnologyA.N. Rajagopalan Indian Institute of Technology, MadrasMubarak Shah University of Central FloridaTakeshi Shakunaga Okayama UniversityDavid Suter Monash UniversityTanveer Syeda-Mahmood IBM Almaden Research CenterChi-Keung Tang Hong Kong University of Science and TechnologyXiaoou Tang Microsoft Research AsiaRin-ichiro Taniguchi Kyushu UniversityBaba Vemuri University of FloridaYaser Yacoob University of MarylandNaokazu Yokoya Nara Institute of Science and TechnologyChangshui Zhang Tsinghua UniversityZhengyou Zhang Microsoft Research, Redmond

Reviewers

Neeharika AdabalaManoj AggarwalAmir AkbarzadehYusuf AkgulKenichi ArakawaGreg ArnoldNaoki AsadaMark AshdownTarkan AydinNoboru BabaguchiSimon BakerHynek BaksteinAlok BandekarSubhashis BanerjeeMusodiq BelloKiran BhatRahul BhotikaPrabir Kumar BiswasMichael BrownSema CandemirLekha ChaisornKap Luk ChanMichael ChanSharat ChandranPeng ChangParag ChaudhuriDatong ChenChu-Song ChenXilin ChenYong-Sheng ChenJames CheongTat-Jun ChinOndrej ChumAntonio CriminisiShengyang Dai

Kristin DanaJames DavisAmadou DialloGianfranco DorettoLingyu DuanSumantra Dutta RoyRyan EckboAlexei EfrosHazim Kemal EkenelSabu EmmanuelChris EngelsMark EveringhamZhimin FanJan-Michael FrahmKazuhiro FukuiHui GaoTheo GeversChristopher GeyerJoshua GluckmanDmitry GoldgofGirish GopalakrishnanRalph GrossYanlin GuoKeiji GyohtenMei HanWang HanziManabu HashimotoJean-Yves HerveShinsaku HiuraJeffrey HoKi-Sang HongAnthony HoogsOsamu HoriKazuhiro HottaChangbo Hu

Gang HuaRui HuangSzu-Hao HuangDaniel HuberSei IkedaAli IskurtC.V. JawaharJiaya JiaSeon Joo KimIoannis KakadiarisAtul KanaujiaMasayuki KanbaraMoon Gi KangSing Bing KangMark KeckZia KhanRon KimmelKoichi KiseDan KongRavi KothariRyo KurazumeUday KurkureJames KwokShang-Hong LaiArvind LakshmikumarShihong LAOKyoung Mu LeeWee Kheng LeowMaylor LeungThomas LeungDahua LiLiyuan LiMin LiLin LiangChia-Te Liao

X Organization

Jenn-Jier James LienJoo-Hwee LimStephen LinChe-Bin LiuZhiheng LiuQingshan LiuTyng-Luh LiuXiaoming LiuZicheng LiuYogish MallyaJose MarroquinDaniel MartinecBogdan MateiYasuyuki MatsushitaScott McClosskeyPaulo MendoncaShabbir MerchantBranislav MicusikKarol MikulaJames MillerAnurag MittalDaisuke MiyazakiKooksang MoonYasuhiro MukaigawaDipti Prasad MukherjeeJayanta MukhopadhyayKartik Chandra

MuktinutalapatiRakesh MullickChristopher NafisAnoop NamboodiriSrinivasa NarasimhanKo NishinoDavid NisterNaoko Nitta

Takahiro OkabeShinichiro OmachiSean O’MaleyTaragay OskiperJiazhi OuDirk PadfieldKannappan PalaniappanVladimir PavlovicShmuel PelegA.G. Amitha PereraMichael PhelpsCarlos PhillipsMarc PollefeysDaniel PooleyArun PujariKokku RaghuDeepu RajanSubrata RakshitSrikumar RamalingamRavi RamamoorthiVisvanathan RameshAnand RangarajanSohan RanjanCen RaoChristopher RasmussenAlex Rav-AchaSai RavelaJens RittscherJames RossAmit Roy-ChowdhuryHideo SaitoSubhajit SanyalAlessandro SartiImari SatoTetsu Sato

Tomokazu SatoYoichi SatoPeter SavadjievKonrad SchindlerAndrew SeniorErdogan SevilgenShiguang ShanYing ShanVinay SharmaZhang ShengSheng-Wen ShihIkuko Shimizu OkataniK.S. ShriramKaleem SiddiqiTerence SimSudipta SinhaJayanthi SivaswamyThitiwan SrinarkS.H. SrinivasanChristopher StaufferJesse StewartHenrik SteweniusSvetlana StolpnerPeter SturmAkihiro SugimotoRahul SukthankarQibin SunSrikanth

SuryanarayanananBharath Kumar SVRahul SwaminathanGokul SwamyKar-Han TanMing TangHai Tao

Organization XI

SriRam ThirthalaYing-Li TianPrithi TissainayagamGeorge TodericiShoji TominagaWai Shun Dickson TongPhilip TorrLorenzo TorresaniEmin TuranalpAmbrish TyagiSeiichi UchidaNorimichi UkitaAnton van den HengelRajashekar VenkatachalamSvetha VenkateshUlas VuralToshikazu WadaMeng WanHuan WangLiang WangShu-Fan WangChieh-Chih (Bob) WangZhizhou WangTomas WernerFrederick WheelerKwan-Yee Kenneth WongWoontack WooWen WuYihong WuYing WuJing XiaoJiangjian XiaoWei Xu

Yasushi YagiShuntaro YamazakiKazumasa YamazawaShuicheng YanHua YangMing YangChangjiang YangJie YangMing-Hsuan YangRuigang YangQingxiong YangJieping YeDit-Yan YeungTing YuXinguo YuJingyi YuAli ZandifarXiang ZhangHongming ZhangLi ZhangTao ZhaoWenyi ZhaoJiang Yu ZhengWei ZhouYongwei ZhuAndrew ZissermanLarry Zitnick

Table of Contents – Part II

Infinite Homography Estimation Using Two Arbitrary PlanarRectangles

Jun-Sik Kim, In So Kweon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Shape OrientabilityJovisa Zunic, Paul L. Rosin, Lazar Kopanja . . . . . . . . . . . . . . . . . . . . . . 11

How to Compute the Pose of an Object Without a Direct View?Peter Sturm, Thomas Bonfort . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Dense Motion and Disparity Estimation Via Loopy Belief PropagationMichael Isard, John MacCormick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

A Real-Time Large Disparity Range Stereo-System Using FPGAsDivyang K. Masrani, W. James MacLean . . . . . . . . . . . . . . . . . . . . . . . . 42

Use of a Dense Surface Point Distribution Model in a Three-StageAnatomical Shape Reconstruction from Sparse Information forComputer Assisted Orthopaedic Surgery: A Preliminary Study

Guoyan Zheng, Kumar T. Rajamani, Lutz-Peter Nolte . . . . . . . . . . . . 52

Fisheye Lenses Calibration Using Straight-Line Spherical PerspectiveProjection Constraint

Xianghua Ying, Zhanyi Hu, Hongbin Zha . . . . . . . . . . . . . . . . . . . . . . . . 61

Robust Linear Auto-calibration of a Moving Camera from ImageSequences

Thorsten Thormahlen, Hellward Broszio, Patrick Mikulastik . . . . . . . . 71

Frame Rate Stabilization by Variable Resolution Shape Reconstructionfor On-Line Free-Viewpoint Video Generation

Rui Nabeshima, Megumu Ueda, Daisaku Arita,Rin-ichiro Taniguchi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Vision-Based Posing of 3D Virtual ActorsAmeya S.Vaidya, Appu Shaji, Sharat Chandran . . . . . . . . . . . . . . . . . . . 91

Super-Resolved Video Mosaicing for Documents Based on ExtrinsicCamera Parameter Estimation

Akihiko Iketani, Tomokazu Sato, Sei Ikeda, Masayuki Kanbara,Noboru Nakajima, Naokazu Yokoya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

XIV Table of Contents – Part II

Content Based Image and Video Retrieval Using Embedded TextChinmaya Misra, Shamik Sural . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

Object Tracking Using Background Subtraction and Motion Estimationin MPEG Videos

Ashwani Aggarwal, Susmit Biswas, Sandeep Singh, Shamik Sural,A.K. Majumdar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121

Multi-camera Tracking of Articulated Human Motion Using Motionand Shape Cues

Aravind Sundaresan, Rama Chellappa . . . . . . . . . . . . . . . . . . . . . . . . . . . 131

Matching Gait Image Sequences in the Frequency Domain for TrackingPeople at a Distance

Ryusuke Sagawa, Yasushi Makihara, Tomio Echigo,Yasushi Yagi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141

Performance Evaluation of Object Detection and Tracking in VideoVasant Manohar, Padmanabhan Soundararajan, Harish Raju,Dmitry Goldgof, Rangachar Kasturi, John Garofolo . . . . . . . . . . . . . . . 151

Vehicle Detection Using Double Slit CameraShunji Katahara, Masayoshi Aoki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162

Automatic Vehicle Detection Using Statistical ApproachChi-Chen Raxle Wang, Jenn-Jier James Lien . . . . . . . . . . . . . . . . . . . . 171

A Handheld Projector Supported by Computer VisionAkash Kushal, Jeroen van Baar, Ramesh Raskar,Paul Beardsley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

FormPad: A Camera-Assisted Digital NotepadTanveer Syeda-Mahmood, Thomas Zimmerman . . . . . . . . . . . . . . . . . . . 193

Symmetric Color Ratio in Spiral ArchitectureWenjing Jia, Huaifeng Zhang, Xiangjian He, Qiang Wu . . . . . . . . . . . 204

A Geometric Contour Framework with Vector Field SupportZhenglong Li, Qingshan Liu, Hanqing Lu . . . . . . . . . . . . . . . . . . . . . . . . 214

Clustering Spherical Shells by a Mini-Max Information AlgorithmXulei Yang, Qing Song, Wenbo Zhang, Zhimin Wang . . . . . . . . . . . . . . 224

Clustering of Interval-Valued Symbolic Patterns Based on MutualSimilarity Value and the Concept of k-Mutual Nearest Neighborhood

D.S. Guru, H.S. Nagendraswamy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234

Table of Contents – Part II XV

Multiple Similarities Based Kernel Subspace Learning for ImageClassification

Wang Yan, Qingshan Liu, Hanqing Lu, Songde Ma . . . . . . . . . . . . . . . 244

Detection and Applications

Boosted Algorithms for Visual Object Detection on Graphics ProcessingUnits

Hicham Ghorayeb, Bruno Steux, Claude Laurgeau . . . . . . . . . . . . . . . . . 254

Combining Iterative Inverse Filter with Shock Filter for BaggageInspection Image Deblurring

Guoqiang Yu, Jin Zhang, Li Zhang, Zhiqiang Chen,Yuanjing Li . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264

Automatic Chromosome Classification Using Medial AxisApproximation and Band Profile Similarity

Jau Hong Kao, Jen Hui Chuang, Tsai Pei Wang . . . . . . . . . . . . . . . . . 274

Object Detection Using a Cascade of 3D ModelsHon-Keat Pong, Tat-Jen Cham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284

Heuristic Pre-clustering Relevance Feedback in Region-Based ImageRetrieval

Wan-Ting Su, Wen-Sheng Chu, Jenn-Jier James Lien . . . . . . . . . . . . . 294

Biologically Motivated Perceptual Feature: Generalized RobustInvariant Feature

Sungho Kim, In So Kweon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305

Statistics and Kernels

A Framework for 3D Object Recognition Using the Kernel ConstrainedMutual Subspace Method

Kazuhiro Fukui, Bjorn Stenger, Osamu Yamaguchi . . . . . . . . . . . . . . . . 315

An Iterative Method for Preserving Edges and Reducing Noise in HighResolution Image Reconstruction

Chanho Jung, Gyeonghwan Kim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325

Fast Binary Dilation/Erosion Algorithm Using KernelSubdivision

Ajay Narayanan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335

XVI Table of Contents – Part II

Fast Global Motion Estimation Via Iterative Least-Square MethodJia Wang, Haifeng Wang, Qingshan Liu, Hanqing Lu . . . . . . . . . . . . . 343

Kernel-Based Robust Tracking for Objects Undergoing OcclusionR. Venkatesh Babu, Patrick Perez, Patrick Bouthemy . . . . . . . . . . . . . 353

Adaptive Object Tracking with Online Statistical Model UpdateKaiYeuh Chang, Shang-Hong Lai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363

Segmentation

Inducing Semantic Segmentation from an ExampleYaar Schnitman, Yaron Caspi, Daniel Cohen-Or,Dani Lischinski . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373

Super Resolution Using Graph-CutUma Mudenagudi, Ram Singla, Prem Kalra, Subhashis Banerjee . . . . 385

A Multiphase Level Set Based Segmentation Framework with PoseInvariant Shape Priors

Michael Fussenegger, Rachid Deriche, Axel Pinz . . . . . . . . . . . . . . . . . . 395

A Unified Framework for Segmentation-Assisted Image RegistrationJundong Liu, Yang Wang, Junhong Liu . . . . . . . . . . . . . . . . . . . . . . . . . . 405

Geometry and Statistics

Fusion of 3D and Appearance Models for Fast Object Detection andPose Estimation

Hesam Najafi, Yakup Genc, Nassir Navab . . . . . . . . . . . . . . . . . . . . . . . . 415

Efficient 3D Face Reconstruction from a Single 2D Image by CombiningStatistical and Geometrical Information

Shu-Fan Wang, Shang-Hong Lai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 427

Multiple View Geometry in the Space-TimeKazutaka Hayakawa, Jun Sato . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437

Detecting Critical Configuration of Six PointsYihong Wu, Zhanyi Hu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447

Robustness in Motion AveragingVenu Madhav Govindu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457

Table of Contents – Part II XVII

Signal Processing

Detection of Moving Objects by Independent Component AnalysisMasaki Yamazaki, Gang Xu, Yen-Wei Chen . . . . . . . . . . . . . . . . . . . . . . 467

OK-Quantization Theory and Its Relationship to Sampling TheoremYuji Tanaka, Takayuki Fujiwara, Hiroyasu Koshimizu,Taizo Iijima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479

Contour Matching Based on Belief PropagationShiming Xiang, Feiping Nie, Changshui Zhang . . . . . . . . . . . . . . . . . . . . 489

Key Frame-Based Activity Representation Using AntieigenvaluesNaresh P. Cuntoor, Rama Chellappa . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499

Fast Image Replacement Using Multi-resolution ApproachChih-Wei Fang, Jenn-Jier James Lien . . . . . . . . . . . . . . . . . . . . . . . . . . . 509

Poster Session 3

Histogram Features-Based Fisher Linear Discriminant for FaceDetection

Haijing Wang, Peihua Li, Tianwen Zhang . . . . . . . . . . . . . . . . . . . . . . . 521

Perception Based Lighting Balance for Face DetectionXiaoyue Jiang, Pei Sun, Rong Xiao, Rongchun Zhao . . . . . . . . . . . . . . 531

An Adaptive Weight Assignment Scheme in Linear SubspaceApproaches for Face Recognition

Satyanadh Gundimada, Vijayan Asari . . . . . . . . . . . . . . . . . . . . . . . . . . . 541

Template-Based Hand Pose Recognition Using Multiple CuesBjorn Stenger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551

Scalable Representation and Learning for 3D Object Recognition UsingShared Feature-Based View Clustering

Sungho Kim, In So Kweon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561

Video Scene Interpretation Using Perceptual Prominence andMise-en-scene Features

Gaurav Harit, Santanu Chaudhury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 571

Smooth Foreground-Background Segmentation for Video ProcessingKonrad Schindler, Hanzi Wang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 581

XVIII Table of Contents – Part II

Efficient Object Segmentation Using Digital Matting for MPEG VideoSequences

Yao-Tsung Jason Tsai, Jenn-Jier James Lien . . . . . . . . . . . . . . . . . . . . 591

Background Segmentation Beyond RGBFredrik Kristensen, Peter Nilsson, Viktor Owall . . . . . . . . . . . . . . . . . . 602

Classification of Photometric Factors Based on PhotometricLinearization

Yasuhiro Mukaigawa, Yasunori Ishii, Takeshi Shakunaga . . . . . . . . . . . 613

Material Classification Using Morphological Pattern Spectrum forExtracting Textural Features from Material Micrographs

D. Ghosh, David C. Tou Wei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 623

A Hierarchical Framework for Generic Sports Video ClassificationMaheshkumar H. Kolekar, Somnath Sengupta . . . . . . . . . . . . . . . . . . . . 633

Feature Detection with an Improved Anisotropic FilterMohamed Gobara, David Suter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 643

Feature Selection for Image CategorizationFeng Xu, Yu-Jin Zhang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653

An Energy Minimization Process for Extracting Eye Feature Based onDeformable Template

Huachun Tan, Yu-Jin Zhang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663

Image Feature Detection as Robust Model FittingDengfeng Chai, Qunsheng Peng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 673

Extraction of Salient Contours Via Excitatory-Inhibitory Interactionsin the Visual Cortex

Qiling Tang, Nong Sang, Tianxu Zhang . . . . . . . . . . . . . . . . . . . . . . . . . . 683

Identification of Printing Process Using HSV Colour SpaceHaritha Dasari, Chakravarthy Bhagvati . . . . . . . . . . . . . . . . . . . . . . . . . . 692

Spatiotemporal Density Feature Analysis to Detect Liver Cancer fromAbdominal CT Angiography

Yoshito Mekada, Yuki Wakida, Yuichiro Hayashi, Ichiro Ide,Hiroshi Murase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 702

Fast Block Matching Algorithm in Walsh Hadamard DomainNgai Li, Chun-Man Mak, Wai-Kuen Cham . . . . . . . . . . . . . . . . . . . . . . 712

Table of Contents – Part II XIX

Skin Detection by Near Infrared Multi-band for Driver Support SystemYasuhiro Suzuki, Kazuhiko Yamamoto, Kunihito Kato,Michinori Andoh, Shinichi Kojima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 722

Extracting Surface Representations from Rim CurvesHai Chen, Kwan-Yee K. Wong, Chen Liang, Yue Chen . . . . . . . . . . . . 732

Applying Non-stationary Noise Estimation to Achieve ContrastInvariant Edge Detection

Paul Wyatt, Hiroaki Nakai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 742

Corner Detection Using Morphological Skeleton: An Efficient andNonparametric Approach

R. Dinesh, D.S. Guru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 752

Correspondence Search in the Presence of Specular Highlights UsingSpecular-Free Two-Band Images

Kuk-Jin Yoon, In-So Kweon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 761

Stereo Matching Algorithm Using a Weighted Average of CostsAggregated by Various Window Sizes

Kan’ya Sasaki, Seiji Kameda, Atsushi Iwata . . . . . . . . . . . . . . . . . . . . . . 771

Pseudo Measurement Based Multiple Model Approach for RobustPlayer Tracking

Xiaopin Zhong, Nanning Zheng, Jianru Xue . . . . . . . . . . . . . . . . . . . . . 781

A Hierarchical Method for 3D Rigid Motion EstimationThitiwan Srinark, Chandra Kambhamettu, Maureen Stone . . . . . . . . . 791

Virtual Fashion Show Using Real-Time Markerless Motion CaptureRyuzo Okada, Bjorn Stenger, Tsukasa Ike, Nobuhiro Kondoh . . . . . . . 801

Space-Time Invariants for 3D Motions from Projective CamerasYing Piao, Jun Sato . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 811

Detecting and Tracking Distant Objects at Night Based on HumanVisual System

Kaiqi Huang, Liangsheng Wang, Tieniu Tan . . . . . . . . . . . . . . . . . . . . . 822

Motion Guided Video Sequence SynchronizationDaniel Wedge, Du Huynh, Peter Kovesi . . . . . . . . . . . . . . . . . . . . . . . . . 832

Landmark Based Global Self-localization of Mobile Soccer RobotsAbdul Bais, Robert Sablatnig . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 842

XX Table of Contents – Part II

Self-calibration Based 3D Information Extraction and Application inBroadcast Soccer Video

Yang Liu, Dawei Liang, Qingming Huang, Wen Gao . . . . . . . . . . . . . . 852

Error Analysis of SFM Under Weak-Perspective ProjectionLoong-Fah Cheong, Shimiao Li . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 862

General Specular Surface TriangulationThomas Bonfort, Peter Sturm, Pau Gargallo . . . . . . . . . . . . . . . . . . . . . 872

Dense 3D Reconstruction with an Uncalibrated Active StereoSystem

Hiroshi Kawasaki, Yutaka Ohsawa, Ryo Furukawa,Yasuaki Nakamura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 882

Surface-Independent Direct-Projected Augmented RealityHanhoon Park, Moon-Hyun Lee, Sang-Jun Kim,Jong-Il Park . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 892

Aspects of Optimal Viewpoint Selection and Viewpoint FusionFrank Deinzer, Joachim Denzler, Christian Derichs,Heinrich Niemann . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 902

An Efficient Approach for Multi-view Face Animation Based on Quasi3D Model

Yanghua Liu, Guangyou Xu, Linmi Tao . . . . . . . . . . . . . . . . . . . . . . . . . 913

Hallucinating 3D FacesShiqi Peng, Gang Pan, Shi Han, Yueming Wang . . . . . . . . . . . . . . . . . . 923

High Quality Compression of Educational Videos UsingContent-Adaptive Framework

Ankush Mittal, Ankur Jain, Sourabh Jain,Sumit Gupta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 933

Video Processing

Double Regularized Bayesian Estimation for Blur Identification inVideo Sequences

Hongwei Zheng, Olaf Hellwich . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 943

A Multi-Layer MRF Model for Video Object SegmentationZoltan Kato, Ting-Chuen Pong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 953

Table of Contents – Part II XXI

Scene Interpretation: Unified Modeling of Visual Context byParticle-Based Belief Propagation in Hierarchical Graphical Model

Sungho Kim, In So Kweon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 963

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 973

Table of Contents – Part I

Camera Calibration

On Using Silhouettes for Camera CalibrationEdmond Boyer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Towards a Guaranteed Solution to Plane-Based Self-calibrationBenoıt Bocquillon, Pierre Gurdjos, Alain Crouzil . . . . . . . . . . . . . . . . . . 11

Plane-Based Calibration and Auto-calibration of a Fish-Eye CameraHongdong Li, Richard Hartley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Stereo and Pose

Stereo Matching Using Iterated Graph Cuts and Mean Shift FilteringJu Yong Chang, Kyoung Mu Lee, Sang Uk Lee . . . . . . . . . . . . . . . . . . . 31

Augmented Stereo PanoramasChien-Wei Chen, Li-Wei Chan, Yu-Pao Tsai, Yi-Ping Hung . . . . . . . 41

A Local Basis Representation for Estimating Human Pose fromCluttered Images

Ankur Agarwal, Bill Triggs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Alignment of 3D Models to Images Using Region-Based MutualInformation and Neighborhood Extended Gaussian Images

Hon-Keat Pong, Tat-Jen Cham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

Texture

The Eigen-Transform and ApplicationsAlireza Tavakoli Targhi, Eric Hayman, Jan-Olof Eklundh,Mehrdad Shahshahani . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Edge-Model Based Representation of Laplacian SubbandsMalay K. Nema, Subrata Rakshit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Fusion of Texture Variation and On-Line Color Sampling for MovingObject Detection Under Varying Chromatic Illumination

Chunfeng Shen, Xueyin Lin, Yuanchun Shi . . . . . . . . . . . . . . . . . . . . . . 90

XXIV Table of Contents – Part I

Combining Microscopic and Macroscopic Information for Rotation andHistogram Equalization Invariant Texture Classification

S. Liao, W.K. Law, Albert C.S. Chung . . . . . . . . . . . . . . . . . . . . . . . . . . 100

Poster Session 1

Gaussian Decomposition for Robust Face RecognitionFumihiko Sakaue, Takeshi Shakunaga . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

Occlusion Invariant Face Recognition Using Selective LNMF BasisImages

Hyun Jun Oh, Kyoung Mu Lee, Sang Uk Lee,Chung-Hyuk Yim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

Two-Dimensional Fisher Discriminant Analysis and Its Application toFace Recognition

Zhizheng Liang, Pengfei Shi, David Zhang . . . . . . . . . . . . . . . . . . . . . . . 130

Combining Geometric and Gabor Features for Face RecognitionP.S. Hiremath, Ajit Danti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140

Complex Activity Representation and Recognition by ExtendedStochastic Grammar

Zhang Zhang, Kaiqi Huang, Tieniu Tan . . . . . . . . . . . . . . . . . . . . . . . . . 150

Recognize Multi-people Interaction Activity by PCA-HMMsYing Wang, Xinwen Hou, Tieniu Tan . . . . . . . . . . . . . . . . . . . . . . . . . . . 160

Object Recognition Through the Principal Component Analysis ofSpatial Relationship Amongst Lines

B.H. Shekar, D.S. Guru, P. Nagabhushan . . . . . . . . . . . . . . . . . . . . . . . . 170

Shift-Invariant Image Denoising Using Mixture of Laplace Distributionsin Wavelet-Domain

B.S. Raghavendra, P. Subbanna Bhat . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180

Blind Watermarking Via Pixel Modification with Regular RuleYulin Wang, Jinxu Guo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189

Surface Interpolation by Adaptive Neuro-fuzzy Inference System BasedLocal Ordinary Kriging

Coskun Ozkan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196

PCA-Based Recognition for Efficient InpaintingThommen Korah, Christopher Rasmussen . . . . . . . . . . . . . . . . . . . . . . . . 206

Table of Contents – Part I XXV

Texture Image Segmentation: An Interactive Framework Based onAdaptive Features and Transductive Learning

Shiming Xiang, Feiping Nie, Changshui Zhang . . . . . . . . . . . . . . . . . . . . 216

Image Segmentation That Merges Together Boundary and RegionInformation

Wei Wang, Ronald Chung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226

Extraction of Main Urban Roads from High Resolution Satellite Imagesby Machine Learning

Yanqing Wang, Yuan Tian, Xianqing Tai, Lixia Shu . . . . . . . . . . . . . . 236

Texture Classification Using a Novel, Soft-Set Theory BasedClassification Algorithm

Milind M. Mushrif, S. Sengupta, A.K. Ray . . . . . . . . . . . . . . . . . . . . . . . 246

Learning Multi-category Classification in Bayesian FrameworkAtul Kanaujia, Dimitris Metaxas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255

Estimation of Structural Information Content in ImagesSubrata Rakshit, Anima Mishra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265

Automatic Moving Object Segmentation with Accurate BoundariesJia Wang, Haifeng Wang, Qingshan Liu, Hanqing Lu . . . . . . . . . . . . . 276

A Bottom up Algebraic Approach to Motion SegmentationDheeraj Singaraju, Rene Vidal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286

A Multiscale Co-linearity Statistic Based Approach to RobustBackground Modeling

Prithwijit Guha, Dibyendu Palai, K.S. Venkatesh,Amitabha Mukerjee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297

Motion Detection in Driving Environment Using U-V-DisparityJia Wang, Zhencheng Hu, Hanqing Lu, Keiichi Uchimura . . . . . . . . . . 307

Visual Surveillance Using Less ROIs of Multiple Non-calibrated CamerasTakashi Nishizaki, Yoshinari Kameda, Yuichi Ohta . . . . . . . . . . . . . . . . 317

A Novel Robust Statistical Method for Background Initialization andVisual Surveillance

Hanzi Wang, David Suter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328

Exemplar-Based Human Contour TrackingShiming Xiang, Feiping Nie, Changshui Zhang . . . . . . . . . . . . . . . . . . . . 338

XXVI Table of Contents – Part I

Tracking Targets Via Particle Based Belief PropagationJianru Xue, Nanning Zheng, Xiaopin Zhong . . . . . . . . . . . . . . . . . . . . . 348

Multiple-Person Tracking Using a Plan-View Map with Error EstimationKentaro Hayashi, Takahide Hirai, Kazuhiko Sumi,Koichi Sasakawa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359

Extrinsic Camera Parameter Estimation Based-on Feature Trackingand GPS Data

Yuji Yokochi, Sei Ikeda, Tomokazu Sato, Naokazu Yokoya . . . . . . . . . . 369

A Method for Calibrating a Motorized Object RigPang-Hung Huang, Yu-Pao Tsai, Wan-Yen Lo, Sheng-Wen Shih,Chu-Song Chen, Yi-Ping Hung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379

Calibration of Rotating Line Camera for Spherical ImagingTomoyuki Hirota, Hajime Nagahara, Masahiko Yachida . . . . . . . . . . . . 389

Viewpoint Determination of Image by Interpolation over Sparse SamplesBodong Liang, Ronald Chung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399

Inverse Volume Rendering Approach to 3D Reconstruction fromMultiple Images

Shuntaro Yamazaki, Masaaki Mochimaru, Takeo Kanade . . . . . . . . . . . 409

Gaze Direction Estimation with a Single Camera Based on FourReference Points and Three Calibration Images

Shinjiro Kawato, Akira Utsumi, Shinji Abe . . . . . . . . . . . . . . . . . . . . . . . 419

3D Shape Recovery of Smooth Surfaces: Dropping the Fixed ViewpointAssumption

Yael Moses, Ilan Shimshoni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429

Stereo Matching by InterpolationBodong Liang, Ronald Chung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439

Novel View Synthesis Using Locally Adaptive Depth RegularizationHitesh Shah, Subhasis Chaudhuri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449

View Synthesis of Scenes with Multiple Independently TranslatingObjects from Uncalibrated Views

Geetika Sharma, Santanu Chaudhury, J.B. Srivastava . . . . . . . . . . . . . 460

Generating Free Viewpoint Images from Mutual Projection of CamerasKoichi Kato, Jun Sato . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 470

Table of Contents – Part I XXVII

Video Synthesis with High Spatio-temporal Resolution Using MotionCompensation and Image Fusion in Wavelet Domain

Kiyotaka Watanabe, Yoshio Iwai, Hajime Nagahara,Masahiko Yachida, Toshiya Suzuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480

Estimating Illumination Parameters in Real Space with Application toImage Relighting

Feng Xie, Linmi Tao, Guangyou Xu, Huijun Di . . . . . . . . . . . . . . . . . . 490

An Efficient Real Time Low Bit Rate Video CodecShikha Tripathi, R. Vikas, R.C. Jain . . . . . . . . . . . . . . . . . . . . . . . . . . . . 500

Employing a Fish-Eye for Scene Tunnel ScanningJiang Yu Zheng, Shigang Li . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 509

Automatically Building 2D Statistical Shapes Using the TopologyPreservation Model GNG

Jose Garcıa Rodrıguez, Anastassia Angelopoulou,Alexandra Psarrou, Kenneth Revett . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519

Semi-metric Space: A New Approach to Treat Orthogonality andParallelism

Jun-Sik Kim, In So Kweon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529

Face Recognition

Boosting Multi-gabor Subspaces for Face RecognitionQingShan Liu, HongLiang Jin, XiaoOu Tang, HanQing Lu,SongDe Ma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 539

A New Distance Criterion for Face Recognition Using Image SetsTat-Jun Chin, David Suter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549

Face-Voice Authentication Based on 3D Face ModelsGirija Chetty, Michael Wagner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 559

Face Recognition Under Varying Illumination Based on MAPEstimation Incorporating Correlation Between Surface Points

Mihoko Shimano, Kenji Nagao, Takahiro Okabe, Imari Sato,Yoichi Sato . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 569

Exploring Facial Expression Effects in 3D Face Recognition UsingPartial ICP

Yueming Wang, Gang Pan, Zhaohui Wu, Yigang Wang . . . . . . . . . . . 581

XXVIII Table of Contents – Part I

Vision Based Speech Animation Transferring with UnderlyingAnatomical Structure

Yuru Pei, Hongbin Zha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591

Variational Methods

A Level Set Approach for Shape Recovery of Open ContoursMin Li, Chandra Kambhamettu, Maureen Stone . . . . . . . . . . . . . . . . . . 601

Statistical Shape Models Using Elastic-String RepresentationsAnuj Srivastava, Aastha Jain, Shantanu Joshi,David Kaziska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 612

Minimal Weighted Local Variance as Edge Detector for Active ContourModels

W.K. Law, Albert C.S. Chung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 622

A New Active Contour Model: Curvature Gradient Vector FlowJifeng Ning, Chengke Wu, Shigang Liu, Peizhi Wen . . . . . . . . . . . . . . . 633

Dynamic Open Contours Using Particle Swarm Optimization withApplication to Fluid Interface Extraction

M. Thomas, S.K. Misra, C. Kambhamettu, J.T. Kirby . . . . . . . . . . . . 643

Attractor-Guided Particle Filtering for Lip Contour TrackingYong-Dian Jian, Wen-Yan Chang, Chu-Song Chen . . . . . . . . . . . . . . . . 653

Tracking

Tracking with the Kinematics of Extremal ContoursDavid Knossow, Remi Ronfard, Radu Horaud,Frederic Devernay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 664

Multiregion Level Set Tracking with Transformation Invariant ShapePriors

Michael Fussenegger, Rachid Deriche, Axel Pinz . . . . . . . . . . . . . . . . . . 674

Multi-view Object Tracking Using Sequential Belief PropagationWei Du, Justus Piater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 684

Online Updating Appearance Generative Mixture Model for MeanshiftTracking

Jilin Tu, Hai Tao, Thomas Huang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 694

Table of Contents – Part I XXIX

Geometry and Calibration

Theory and Calibration for Axial CamerasSrikumar Ramalingam, Peter Sturm, Suresh K. Lodha . . . . . . . . . . . . . 704

Error Characteristics of SFM with Erroneous Focal LengthLoong-Fah Cheong, Xu Xiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 714

Interpreting Sphere Images Using the Double-Contact TheoremXianghua Ying, Hongbin Zha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 724

New 3D Fourier Descriptors for Genus-Zero Mesh ObjectsHongdong Li, Richard Hartley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 734

Lighting and Focus

High Dynamic Range Global MosaicDae-Woong Kim, Ki-Sang Hong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 744

Image-Based Calibration of Spatial Domain Depth-from-Defocus andApplication to Automatic Focus Tracking

Soon-Yong Park, Jaekyoung Moon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 754

Effects of Image Segmentation for Approximating Object AppearanceUnder Near Lighting

Takahiro Okabe, Yoichi Sato . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 764

Fast Feature Extraction Using Approximations to Derivatives withSummed-Area Images

Paul Wyatt, Hiroaki Nakai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 776

Poster Session 2

Detecting Faces from Low-Resolution ImagesShinji Hayashi, Osamu Hasegawa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 787

Human Distribution Estimation Using Shape Projection Model Basedon Multiple-Viewpoint Observations

Akira Utsumi, Hirotake Yamazoe, Ken-ichi Hosaka, Seiji Igi . . . . . . . 797

Modelling the Effect of View Angle Variation on Appearance-BasedGait Recognition

Shiqi Yu, Daoliang Tan, Tieniu Tan . . . . . . . . . . . . . . . . . . . . . . . . . . . . 807

XXX Table of Contents – Part I

Gesture Recognition Using Quadratic CurvesQiulei Dong, Yihong Wu, Zhanyi Hu . . . . . . . . . . . . . . . . . . . . . . . . . . . . 817

From Motion Patterns to Visual Concepts for Event Analysis inDynamic Scenes

Lun Xin, Tieniu Tan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 826

Probabilistic Modeling for Structural Change InferenceWei Liu, Veronique Prinet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 836

Robust Occluded Shape RecognitionRonak Shah, Anima Mishra, Subrata Rakshit . . . . . . . . . . . . . . . . . . . . . 847

Interactive Contour Extraction Using NURBS-HMMDebin Lei, Chunhong Pan, Qing Yang, Minyong Shi . . . . . . . . . . . . . . . 858

Learning Parameter Tuning for Object ExtractionXiongcai Cai, Arcot Sowmya, John Trinder . . . . . . . . . . . . . . . . . . . . . . 868

Region-Level Motion-Based Foreground Detection with ShadowRemoval Using MRFs

Shih-Shinh Huang, Li-Chen Fu, Pei-Yung Hsiao . . . . . . . . . . . . . . . . . . 878

Waterfall Segmentation of Complex ScenesAllan Hanbury, Beatriz Marcotegui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 888

Markovian Framework for Foreground-Background-Shadow Separationof Real World Video Scenes

Csaba Benedek, Tamas Sziranyi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 898

Separation of Reflection and Transparency Using Epipolar Plane ImageAnalysis

Thanda Oo, Hiroshi Kawasaki, Yutaka Ohsawa, Katsushi Ikeuchi . . . 908

Fast Approximated SIFTMichael Grabner, Helmut Grabner, Horst Bischof . . . . . . . . . . . . . . . . . 918

Image Matching by Multiscale Oriented Corner CorrelationFeng Zhao, Qingming Huang, Wen Gao . . . . . . . . . . . . . . . . . . . . . . . . . 928

Surface Registration Using Extended Polar MapsElsayed E. Hemayed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 938

Multiple Range Image Registration by Matching Local Log-PolarRange Images

Takeshi Masuda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 948

Table of Contents – Part I XXXI

Incremental Mesh-Based Integration of Registered Range Images:Robust to Registration Error and Scanning Noise

Hong Zhou, Yonghuai Liu, Longzhuang Li . . . . . . . . . . . . . . . . . . . . . . . 958

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 969