2012 19th IEEE International

Conference on Image Processing

(ICIP 2012)

Orlando, Florida, USA

30 September - 3 October 2012

Pages 789-1556

IIEIEIE IEEE Catalog Number:

ISBN:

CFP12CIP-PRT

978-1-4673-2534-9

2/4

MP-P2.12: ACTION RECOGNITION IN STILL IMAGES USING A COMBINATION OF

HUMAN POSE AND CONTEXT INFORMATION

Yin Zheng, Yu-Jin Zhang, Xue Li, Bao-Di Liu, Tsinghua University, China

.785

MP-P3: DOCUMENT IMAGING & PRINTING

MP-P3.1: ANEWFRAMEWORK FOR AUTOMATIC QUALITY ASSESSMENT OFPRINT 789

MEDIA

Mohan Liu, Fraunhofer Heinrich-Hertz-lnstitute, Germany; Iuliu Konya, Fraunhofer Institute IAIS, Germany;Jan Nandzik, Nicolas Flores-Herr, Acosta Consult GmbH, Germany; Stefan Eickeler, Fraunhofer Institute IAIS,

Germany; Patrick Ndjiki-Nya, Fraunhofer Heinrich-Hertz-lnstitute, Germany

MP-P3.2: OPTICAL CHARACTERRECOGNITION WITHFASTTRAININGNEURAL N/A

NETWORK

Huei-Yung Lin, Chin-Yu Hsu, National Chung Cheng University, Taiwan

MP-P3.3: FAST TEXT LINE EXTRACTION INDOCUMENT IMAGES 797

Seong Jong Ha, Bora Jin, Nam Ik Cho, Seoul National University, Republic ofKorea

MP-P3.4: WHITE PATCH GAMUTMAPPING COLOURCONSTANCY 801

Hamid Reza Vaezi Joze, Mark Drew, Simon Fraser University, Canada

MP-P3.5: VECTORIZING LINE DRAWINGS WITHNEAR-CONSTANT LINE WIDTH 805

Bin Bao, Hongbo Fu, City University ofHong Kong, Hong Kong SAR of China

MP-P3.6: ADAPTIVE COLOR-TO-GRAY IMAGEMAPPING USING DIRECTIONAL.

809

TRANSFORM

Yuko Miyashita, Utsunomiya University, Japan; Yuichi Tanaka, Tokyo University ofAgriculture and

Technology, Japan; Madoka Hasegawa, Shigeo Kato, Utsunomiya University, Japan

MP-P3.7: HIGHEFFICIENT DIRECT BINARY SEARCH USING MULTD7LE LOOKUP 813

TABLES

Jing-Ming Guo, Yun-Fu Liu, Jla-Yu Chang, National Taiwan University ofScience and Technology, Taiwan

MP-P3.8: DBRECTMULTI-BIT SEARCH (DMS) SCREEN ALGORITHM 817

Kartheek Chandu, Mikel Stanich, Ricoh Production Print Solutions, LLC, United States; Chai Wah Wu, Barry

Trager, IBM T.J. Watson Research Center, United States

MP-P3.9: HEVC-BASED SCANNED DOCUMENT COMPRESSION... 821

Alexandre Zaghetto, Bruno Macchiavello, Ricardo de Queiroz, Universidade de Brasilia, Brazil

MP-P3.10: THEIMPORTANCE OF THE NORMALIZING CHANNEL IN 825

LOG-CHROMATICITY SPACE

Eva Eibenberger, Elli Angelopoulou, University of Erlangen-Nuremberg, Germany

MP-P3.11: MULTILEVEL HALFTONE SCREEN DESIGN: KEEPING TEXTURE OR 829

KEEPING SMOOTHNESS?

Xujie Zhang, Purdue University, United States; Alex Veis, Robert Ulichney, Hewlett-Packard Company, Israel;Jan Allebach, Purdue University, United States

MP-P3.12: HIGHCONTRAST STOCHASTIC SCREENWATERMARKS FOR COLOR 833

HALFTONE PRINTS

Gaurav Sharma, University ofRochester, United States; Shen-Ge Wang, Xerox Corporation, United States

xxxiv

MP-P3.13: CONTEXTUAL DETECTION OF DRAWN SYMBOLS IN OLD MAPS 837

Jonathan Guyomard, Nicolas Thome, Matthieu Cord, Thierry Artieres, LIP6, France

MP-P4: SUPER RESOLUTION & INTERPOLATION

MP-P4.1: BLOCK-OVERLAP-BASED VALIDITY METRIC FOR HYBRID 841

DE-INTERLACING

Michael Santoro, Ghassan AlRegib, Yucel Altunbasak, Georgia Institute of Technology, United States

MP-P4.2: EXEMPLAR-BASED FRAME RATE UP-CONVERSION WITH CONGRUENT 845

SEGMENTATION

Seong-Gyun Jeong, Chul Lee, Chang-Su Kim, Korea University, Republic ofKorea

MP-P4.3: A GPU-BASED IMPLEMENTATION ON SUPER-RESOLUTION 849

RECONSTRUCTION

Kai Wang, Lifu Wang, Man Lu, Yi Sun, Dalian University of Technology, China; Shuping Zhao, Dalian Ocean

University, China

MP-P4.4: A GRADD2NT GUIDEDDEEMTERLACING ALGORITHM 853

Bora Jin, Jung Gap Kuk, Nam Ik Cho, Seoul National University, Republic ofKorea

MP-P4.5: VIDEO FRAMEINTERPOLATION USING 3-D TOTAL VARIATION 857

REGULARIZED COMPLETION

Zhefei Yu, Zhangyang Wang, Zeng Hu, Qing Ling, Houqiang Li, University ofScience and Technology ofChina, China

MP-P4.6: VIDEO DEINTERLACING WITH CONTROL GRID INTERPOLATION 861

Ragav Venkatesan, Christine Zwart, David Frakes, Arizona State University, United States

MP-P4.7: CONTENT ASPECT RATIO PRESERVING MESH-BASED IMAGE RESIZING 865

Kazu Mishiba, Tottori University, Japan; Masaaki Ikehara, Keio University, Japan; Takeshi Yoshitome, Tottori

University, Japan

MP-P4.8: WEENER BASED SPATIAL RESOLUTION ENHANCEMENT OF MRI 869

SEQUENCES OF THEVOCAL TRACT: A COMPARISONBETWEEN TWO

CORRELATION MODELS

Ana Martins, Nelson Mascarenhas, Universidade Federal de Sao Carlos, Brazil

MP-P4.9: A GRADffiNT BASED NEIGHBORHOOD FILTER FORDISPARITY 873

INTERPOLATION

Vanel Lazcano, Pablo Arias, Universitat Pompeu Fabra, Spain; Gabriele Facciolo, CMLA ENS Cachan,

France; Vicent Caselles, Universitat Pompeu Fabra, Spain

MP-P4.10: VIDEO SUPER-RESOLUTION BASED ON LOCAL INVARIANTFEATURES 877

MATCHING

Renan Ferreira, Edson M. Hung, Ricardo de Queiroz, Universidade de Brasilia, Brazil

MP-P4.11: IMAGE RESOLUTION UP-CONVERSION VIA MAXIMUM A POSTERIORI 881

INTERPOLATOR SEQUENCE ESTIMATION AND VITERBIALGORITHM

Farhang Vedadi, Shahram Shirani, McMaster University, Canada

xxxv

MP-P5: COMPRESSIVE SENSING

MP-P5.1: COMPRESSIVE VIDEO SENSING USING NON-LINEAR MAPPING 885

Xinyu Zhang, Jiangtao Wen, Tsinghua University, China

MP-P5.2: STEREO VIDEO CODING USING DISTRIBUTED COMPRESSIVE 889

SENSING WITH JOINT DICTIONARY

Huihui Bai, Beijing Jiaotong University, China; Mengmeng Zhang, North China University ofTechnology,China; Anhong Wang, Taiyuan University ofScience and Technology, China; Yao Zhao, Beijing Jiaotong

University, China

MP-P5.3: VIDEO COMPRESSIVE SENSING WITH 3-D WAVELET AND 3-D 893

NOISELET

DaoLam, Donald Wunsch, Missouri University ofScience & Technology, United States

MP-P5.4: MULTI-TASK LOW-RANK AND SPARSE MATRIX RECOVERYFORHUMAN 897

MOTIONSEGMENTATION

Xiangyang Wang, Wanggen Wan, Shanghai University, China; Guangcan Liu, National University of

Singapore, Singapore

MP-P5.5: COMPRESSED SENSING BASED IMAGE FORMATION OF SAR/ISAR DATA IN 901

PRESENCE OF BASIS MISMATCH

Ahmed Khwaja, Xiao-Ping Zhang, Ryerson University, Canada

MP-P5.6: ROBUST COMPRESSED SENSING IN GAUSSIAN NOISE ENVIRONMENT 905

BY RESAMPLING WITH REPLACEMENT

Parichat Sermwuthisarn, Chulalongkorn University, Thailand; Duangrat Gansawat, National Electronics and

Computer Technology Center, Thailand; Vorapoj Patanavijit, Assumption University, Thailand; SupatanaAuethavekiat, Chulalongkorn University, Thailand

MP-P5.7: BLOCK-BASEDVARIABLEDENSITY COMPRESSED IMAGE SAMPLING 909

Wei Qiao, Bin Liu, University ofScience and Technology of China, China; Zixiang Xiong, Texas A&M

University, United States; Gonzalo R. Arce, Javier Garcia-Frias, University ofDelaware, United States;

Wenwu Zhu, Tsinghua University, China; Zhisheng Yan, University ofScience and Technology ofChina, China

MP-P5.8: GRADIENT-BASED SURFACE RECONSTRUCTION USING COMPRESSED 913

SENSING

Mohammad Rostami, Oleg Michailovich, Zhou Wang, University of Waterloo, Canada

MP-P5.9: VIDEO RECONSTRUCTION USING COMPRESSED SENSING 917

MEASUREMENTS AND 3D TOTAL VARIATIONREGULARIZATIONFORBIO-

IMAGINGAPPLICATIONS

Yoann Le Montagner, Institut Pasteur, France; Elsa Angelini, Telecom ParisTech, France; Jean-ChristopheOlivo-Marin, Institut Pasteur, France

MP-P5.10: CORRELATED GAUSSIAN DESIGNS FOR COMPRESSIVE IMAGING 921

Nikhil Rao, Robert Nowak, University of Wisconsin - Madison, United States

MP-P5.11: COMPRESSIVE SAMPLING WITHUNKNOWN BLURRING FUNCTION: 925

APPLICATION TO PASSfVE MILLIMETER-WAVE IMAGING

Bruno Amizic, Leonidas Spinoulas, Northwestern University, United States; Rafael Molina, Universidad de

Granada, Spain; Aggelos Katsaggelos, Northwestern University, United States

xxxvi

MP-P5.12: ADAPTIVE COMPRESSED SENSINGFORDEPTHMAP COMPRESSION 929

USING GRAPH-BASED TRANSFORM

Sungwon Lee, Antonio Ortega, University ofSouthern California, UnitedStates

MP-P5.13: JOINT TRACE/TVNORM MINIMIZATION: ANEWEFFICBENT APPROACH 933

FORSPECTRAL COMPRESSIVE IMAGING

Mohammad Golbdbaee, Pierre Vandergheynst, Ecole Polytechnique Fiderale de Lausanne, Switzerland

MP-P5.14: BNVARIANCE OF PRINCIPAL COMPONENTS UNDERLOW-DIMENSIONAL 937

RANDOMPROJECTION OF THE DATA

HanchaoQi, Shannon Hughes, University ofColorado at Boulder, United States

MP-P6: ENHANCEMENT

MP-P6.1: RAINDROPDETECTIONAND REMOVAL USING SALffiNT VISUAL 941

FEATURES

Qi Wu, Carnegie Mellon University, United States; Wende Zhang, General Motors, United States; B. V.K.

Vijaya Kumar, Carnegie Mellon University, United States

MP-P6.2: A CELL-BASED MATTING LAPLACIANFOR CONTRASTENHANCEMENT 945

Chen-Yu Tseng, Sheng-Jyh Wang, National Chiao-Tung University, Taiwan

MP-P6.3: SPATIALLY ADAPTIVE PDES FORROBUST IMAGE SHARPENING 949

El Hadji Diop, Jesus Angulo, Center ofMathematical Morphology, France

MP-P6.4: IMAGEDE-QUANTIZATIONVIA SPATIALLYVARYING SPARSITY PRIOR 953

Pengfei Wan, Oscar C. Au, Ketan Tang, Yuanfang Guo, Hong Kong University ofScience and Technology,

Hong Kong SAR of China

MP-P6.5: NIGHTTIME HAZEREMOVAL USING COLORTRANSFER 957

PRE-PROCESSINGAND DARK CHANNELPRIOR

Soo-Chang Pei, Tzu-Yen Lee, National Taiwan University, Taiwan

MP-P6.6: DETECTING OF CONTRAST OVER-ENHANCEMENT 961

H.D. Cheng, Harbin Institute ofTechnology, China; Utah State University, United States; Yingtao Zhang,School ofComputer Science and Technology, Harbin Institute ofTechnology, China

MP-P6.7: CONTRAST ENHANCEMENTBASED ON LAYERED DD7FERENCE 965

REPRESENTATION

Chulwoo Lee, Chul Lee, Chang-Su Kim, Korea University, Republic ofKorea

MP-P6.8: TEMPORALLY COHERENT REAL-TIME VIDEODEHAZING 969

Jin-Hwan Kim, Won-Dong Jang, Korea University, Republic ofKorea; Yongsup Park, Dong-Hahk Lee, SK

Telecom, Republic ofKorea; Jae-Young Sim, Ulsan National Institute ofScience and Technology, Republic ofKorea; Chang-Su Kim, Korea University, Republic ofKorea

MP-P6.9: INTERNAL NOISE-INDUCED CONTRASTENHANCEMENT OF DARK 973

IMAGES

Rajib Kumar Jha, PDPMIndian Institute ofInformation Technology Jabalpur, India; Rajlaxmi Chouhan,

Prabir Kumar Biswas, Indian Institute ofTechnology Kharagpur, India; Kiyoharu Aizawa, University of Tokyo,

Japan

xxxvii

MP-P6.10: IMAGE DETAIL ENHANCEMENTUSING A DICTIONARY TECHNIQUE 977

Anustup Choudhury, University ofSouthern California, United States; Peter van Beek, Andrew Segall, SharpLaboratories ofAmerica, Inc., United States

MP-P6.11: SPATIO-TEMPORAL TOFDATA ENHANCEMENT BYFUSION 981

Frederic Garcia, Djamila Aouada, University ofLuxembourg, Luxembourg; Bruno Mirbach, IEE S.A.,

Luxembourg; Bjorn Ottersten, University ofLuxembourg, Luxembourg

MP-P6.12: IMPROVINGIMAGE QUALITY IN SMALLANIMAL DIFFUSION TENSOR 985

IMAGING AT7T

Fernando Yepes, Instituto de Investigaciones Biomidicas de Barcelona, IIBB-CSIC, Spain; Yi Lao, Children's

Hospital ofLos Angeles, United States; Pierre Fillard, INRIA Parietal - Neurospin, France; Carles Justicia,

Anna Pianos, Instituto de Investigaciones Biomidicas de Barcelona, IIBB-CSIC, Spain; Marvin D. Nelson,Children's Hospital ofLos Angeles, United States; Guadalupe Soria, Institut d'investigacions Biomediques

August Pi i Sunyer, Spain; Natasha Lepore, University ofSouthern California, United States

MP-P6.13: HAZE FILTERING WITH AERIAL PERSPECTIVE 989

Renjie Gao, Xin Fan, Jielin Zhang, Zhongxuan Luo, Dalian University of Technology, China

MP-P6.14: RESTRICTED GUIDED FILTER WITH SURE-LET-BASED PARAMETER 993

OPTIMIZATION

Cuong Cao Pham, Jae WookJeon, Sungkyunkwan University, Republic ofKorea

MP-P7: OBJECT IDENTIFICATION & RECOGNITION II

MP-P7.1: EFFICIENT MATCHINGS INAUGMENTED REALITYAPPLICATION 997

Wei Guan, Suya You, Ulrich Neumann, University ofSouthern California, United States

MP-P7.2: SCENE TEXT DETECTION WITH SUPERPIXELS AND HIERARCHICAL 1001

MODEL

Gang Zhou, Yuehu Liu, Zhiqiang Tian, XVan Jiaotong University, China

MP-P7.3: AUTOMATIC IDENITFICATION OF PRESCRD7TION DRUGS USING SHAPE 1005

DISTRD3UTION MODELS

Jesus Caban, National Institutes ofHealth, United States; Adrian Rosebrock, University ofMaryland,Baltimore County, United States; Terry Yoo, National Institutes ofHealth, United States

MP-P7.4: VISUAL RHYTHM-BASED PLANKTON DETECTION METHODFOR 1009

BALLASTWATERQUALITY ASSESSMENT

Damian J. Matuszewski, C. Iury O. Martins, Roberto M. Cesar-Jr, University ofSao Paulo (USP), Brazil; J.

Rudi Strickler, University of Wisconsin - Milwaukee, United States; Rubens M. Lopes, University ofSao Paulo

(USP), Brazil

MP-P7.5: ADAPTIVE DENOISING FILTERING FOROBJECT DETECTION 1013

APPLICATIONS

Simone Milani, Riccardo Bernardini, Roberto Rinaldo, University of Udine, Italy

MP-P7.6: ROBUST FRONTALVIEW SEARCH USING MULTI-CAMERA CONSTRAINED 1017

ISOMAP

Chao Wang, Xubo Song, Oregon Health & Science University, United States

xxxviii

MP-P7.7: CORRESPONDENCE-FREE FUNDAMENTALMATRIX FOROBJECT 1021

RECOGNITION

Gutemberg Guerra-Filho, University ofTexas at Arlington, United States

MP-P7.8: PRUNING PHANTOMDETECTIONSFROM MULTIVIEW FOREGROUND 1025

INTERSECTION

JieRen, University ofLiverpool, United Kingdom; Ming Xu, XVan Jiaotong-Liverpool University, China;

Jeremy S Smith, University ofLiverpool, United Kingdom

MP-P7.9: FULL FLOORIDENTDJICATIONIN IMAGES WITH MINIMAL CLOSE 1029

RANGE3D INFORMATION

Gavin Smith, Jeremy Morley, University ofNottingham, Australia

MP-P7.10: PETIOLE SHAPE DETECTIONFORADVANCED LEAF IDENTDJICATION ...1033

Olfa Mzoughi, Itheri Yahiaoui, Nozha Boujemaa, INRIA Rocquencourt, France

MP-P7.11: UNSUPERVISED DETECTION OF SURFACE DEFECTS: A TWO-STEP 1037

APPROACH

Jiwon Choi, ChangickKim, Korea Advanced Institute ofScience and Technology (KAIST), Republic ofKorea

MP-P7.12: EARLY FntE AND SMOKE DETECTION BASED ON COLOUR FEATURES 1041

AND MOTIONANALYSIS

Pietro Morerio, Lucio Marcenaro, Carlo S. Regazzoni, University ofGenoa, Italy; Gianluca Gera,Technoaware s.r.L, Italy

MP-P8: PERCEPTUAL CODING & SALIENCY

MP-P8.1: JUST NOTICEABLE DISTORTION MAPPREDICTION FORPERCEPTUAL 1045

MULTIVIEW VIDEO CODING

Yu Gao, Xiaoyu Xiu, Jie Liang, Simon Fraser University, Canada; Weisi Lin, Nanyang Technological

University, Singapore

MP-P8.2: LIGHTNESS DELUSION: A NEW LOOKFROM COMPRESSIVE SENSING 1049

PERSPECTIVE

Xinke Tang, Yi Li, National ICTAustralia (NICTA), Australia

MP-P8.3: JPEG-BASED PERCEPTUAL IMAGE CODING WITH BLOCK-BASED IMAGE 1053

QUALITY METRIC

LinaJin, Karen Egiazarian, Tampere University ofTechnology, Finland; C.-C. Jay Kuo, University ofSouthern

California, United States

MP-P8.4: PERCEPTUALLY LOSSLESS HIGHDYNAMICRANGE IMAGE 1057

COMPRESSIONWITHJPEG 2000

Yang Zhang, Erik Reinhard, David Bull, University ofBristol, United Kingdom

MP-P8.5: SSPQ - SPATIAL DOMAIN PERCEPTUALIMAGE CODEC BASED ON 1061

SUBSAMPLINGAND PERCEPTUAL QUANTIZATIONZhe Wang, Sven Simon, Michael Klaiber, Silvia Ahmed, Thomas Richter, University ofStuttgart, Germany

xxxix

MP-P8.6: MATCHED-TEXTURE CODING FOR STRUCTURALLY LOSSLESS 1065COMPRESSION

Guoxin Jin, Northwestern University, United States; Yuanhao Zhai, University ofMichigan, United States;Thrasyvoulos Pappas, Northwestern University, United States; David Neuhoff, University ofMichigan, UnitedStates

MP-P8.7: VISUALSALIENCY ESTIMATION USING SUPPORT VALUE TRANSFORM 1069Weibin Yang, Bin Fang, Yuan Yan Tang, Zhaowei Shang, Hengjun Zhao, School of Computer Science,Chongqing University, China

MP-P8.8: SALH5NCY DETECTION VIA STATISTICAL NON-REDUNDANCY 1073Aanchal Jain, Alexander Wong, Paul Fieguth, University of Waterloo, Canada

MP-P8.9: FROM RARENESS TO COMPACTNESS: CONTRAST-AWARE IMAGE 1077SALIENCY DETECTION

Hsin-Ho Yeh, Chu-Song Chen, Academia Sinica, Taiwan

MP-P8.10: DEFECTING VISUAL ATTENTION BY SUBLIMINAL CUES 1081Tai-Hsiang Huang, Yung-Hao Yang, Hsin-ILiao, Su-Ling Yeh, Homer Chen, National Taiwan University,Taiwan

MP-P8.11: SALffiNCY DETECTION BASED ON INTEGRATION OFBOUNDARY AND 1085SOFT-SEGMENTATION

Jing Sun, Huchuan Lu, Shifeng Li, Dalian University of Technology, China

MP-P8.12: AUTOMATIC SALBENCY INSPIRED FOREGROUND OBJECT EXTRACTION 1089FROMVD3EOS

Wei-Te Li, Academia Sinica, Taiwan; Hui-Tang Chang, Hermes Shing Lyu, National Taiwan University,Taiwan; Yu-Chiang Frank Wang, Academia Sinica, Taiwan

t

MP-P8.13: RELATIONAL ENTROPY-BASED SALD3NCY DETECTION INIMAGES AND 1093VIDEOS

Kester Duncan, Sudeep Sarkar, University of South Florida, United States

MP-P8.14: OBJECT-AWARE SALDENCY DETECTION FOR CONSUMER IMAGES 1097Hao Tang, Hewlett-Packard Laboratories, United States

TA-L1: VISUAL SENSOR NETWORKS

TA-L1.1: PRIORITY-BASED CROSS-LAYER OPTIMIZATION FORMULTIHOP 1101DS-CDMA VISUALSENSOR NETWORKS

Eftychia Datsika, Angeliki Katsenou, Lisimachos Kondi, Evangelos Papapetrou, Konstantinos Parsopoulos,University ofloannina, Greece

TA-L1.2: RATE-ACCURACY OPTIMIZATION IN VISUAL WIRELESS SENSOR 1105NETWORKS

Alessandro Redondi, Matteo Cesana, Marco Tagliasacchi, Politecnico di Milano, Italy

TA-L1.3: CONSENSUS-BASED DISTRD3UTED ESTIMATION IN CAMERANETWORKS ......1109Ahmed Kamal, Jay Farrell, Amit Roy-Chowdhury, University of California, Riverside, United States

xl

TA-L1.4: INTERACTIONRECOGNITION IN WIDEAREAS USING AUDIOVISUAL 1113

SENSORS

Murtaza Taj, Andrea Cavallaro, Queen Mary, University ofLondon, United Kingdom

TA-L1.5: QUALITY-DRIVENPOWER CONTROL AND RESOURCE ALLOCATION IN 1117

WIRELESS MULTI-RATE VISUALSENSORNETWORKS

Angeliki Katsenou, Lisimachos Kondi, Konstantinos Parsopoulos, University ofloannina, Greece; Elizabeth

Bentley, Air Force Research Laboratory, United States

TA-L1.6: EVENT-DRIVEN VIDEO CODING FOROUTDOOR WIRELESS 1121

MONITORING CAMERAS

Zichong Chen, Guillermo Barrenetxea, Martin Vetterli, Ecole Polytechnique Fiderale de Lausanne,Switzerland

TA-L2: CLASSIFICATION

TA-L2.1: WAVELET SUBBAND-BASED STEAM DETECTIONBY MULTD7LE KERNEL 1153

LEARNING

Sharmin Nilufar, Nilanjan Ray, Hong Zhang, University ofAlberta, Canada

TA-L2.2: A HISTOGRAM SEMANTIC-BASED DISTANCE FORMULTHUESOLUTION 1157

IMAGE CLASSIFICATION

Camille Kurtz, Nicolas Passat, Pierre Ganqarski, Anne Puissant, University ofStrasbourg, France

TA-L2.3: STRUCTURED SPARSE LINEAR DISCRIMINANT ANALYSIS 1161

Zhen Cui, Chinese Academy ofSciences; HuaQiao University, China; Shiguang Shan, Chinese Academy ofSciences, China; Haihong Zhang, Shihong Lao, Omron Social Solutions Co., LTD., Japan; Xilin Chen, Chinese

Academy ofSciences, China

TA-L2.4: LEARNING PATTERN TRANSFORMATION MANIFOLDS FOR 1165

CLASSD7ICATION

ElifVural, Pascal Frossard, Ecole Polytechnique Federate de Lausanne, Switzerland

TA-L2.5: REGULARIZED ADAPTIVE CLASSD7ICATION BASEDON IMAGE RETRffiVAL 1169

FOR CLUSTERED MICROCALCD7ICATIONS

Hao Jing, Yongyi Yang, Illinois Institute ofTechnology, United States

TA-L2.6: INTRA-CLASSMULTI-OUTPUT REGRESSION BASED SUBSPACEANALYSIS 1173

Karthikeyan Shanmuga Vadivel, Swapna Joshi, Bangalore S. Manjunath, Scott Grafton, University ofCalifornia, Santa Barbara, United States

TA-L2.7: DISCRIMINANT ACTION REPRESENTATION FORVffiW-INVARIANT 1177

PERSON IDENTIFICATION

Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas, Aristotle University ofThessaloniki, Greece

TA-L3: BIOMETRICS & STEGANOGRAPHY

TA-L3.1: IMPROVED PAYLOAD LOCATION FORLSB MATCHING STEGANOGRAPHY 1125

Xinlu Gui, Xiaolong Li, Bin Yang, Peking University, China

xli

TA-L3.2: TARGETED STEGANALYSIS OFADAPTIVE PIXEL-VALUEDD7FERENCING 1129

STEGANOGRAPHY

Shunquan Tan, Bin Li, Shenzhen University, China

TA-L3.3: STEGANALYSIS BY ENSEMBLE CLASSIFIERS WITHBOOSTING BY 1133

REGRESSION, AND POST-SELECTION OF FEATURES

Marc Chaumont, Sarra Kouider, LIRMM: Laboratoire d'lnformatique, de Robotique et de Microelectroniquede Montpellier, France

TA-L3.4: CARDIAC ANATOMYAS A BIOMETRIC 1137

Noel Codetta, Jonathan Connell, Nalini Ratha, IBM, United States; Jonathan Weinsaft, Weill Cornell Medical

College, United States

TA-L3.5: FUSION OF FINGER VEIN ANDFINGER DORSAL TEXTURE FOR 1141

PERSONALroENTDTICATION BASED ON COMPARATIVE COMPETITIVE

CODING

Wenming Yang, Xiaola Huang, Qingmin Liao, Tsinghua University, China

TA-L3.6: LATENTFINGERPRINT DETECTION AND SEGMENTATIONWITH A.

1145

DDJECTIONAL TOTAL VARIATIONMODEL

Jiangyang Zhang, Rongjie Lai, C.-C. Jay Kuo, University ofSouthern California, United States

TA-L3.7: CORRECTION METHODFORNONIDEAL IRIS RECOGNITION 1149

Eliana Frigerio, Marco Marcon, Augusto Sarti, Stefano Tubaro, Politecnico di Milano, Italy

TA-L4: DENOISING

TA-L4.1: IMPROVING DENOISING FILTERS BY OPTIMAL DDTFUSION 1181

Hossein Talebi, Peyman Milanfar, University of California, Santa Cruz, United States

TA-L4.2: HXUMINATION-INVARIANT NON-LOCAL MEANSBASED VTOEO 1185

DENOISING

Jie Ren, Peking University, China; Yue Zhuo, Beijing Normal University, China; Jiaying Liu, Zongming Guo,

Peking University, China

TA-L4.3: DICTIONARY TRANSFERFORIMAGEDENOISING VIA DOMAIN ADAPTATION ...1189

Gang Chen, Caiming Xiong, Jason J. Corso, State University ofNew York at Buffalo, United States

TA-L4.4: COLOR IMAGE DENOISING BASED ON MULTICHANNEL NON-LOCAL 1193

MEANS FUSION

Jingjing Dai, Oscar C. Au, Feng Zou, Chao Pang, Lu Fang, Hong Kong University ofScience and Technology,

Hong Kong SAR ofChina

TA-L4.5: ON THENATURE OF VARIATIONAL SALT-AND-PEPPER NOISE REMOVAL 1197

AND ITS FAST APPROXIMATION

Yi Wan, Jiafa Zhu, Qiqiang Chen, Lanzhou University, China

TA-L4.6: MEASURING NOISE CORRELATION FORIMPROVED VIDEO DENOISING 1201

Anil Kokaram, Damien Kelly, Hugh Denman, Andrew Crawford, Google, Inc., United States

xlii

TA-L4.7: THEUNDECIMATEDDUAL TREECOMPLEX WAVELET TRANSFORMAND 1205

ITS APPLICATION TO BIVARIATE IMAGEDENOISING USING A CAUCHY

MODEL

Paul Hill, Alin Achim, David Bull, University ofBristol, United Kingdom

TA-L5: SEGMENTATION & DEPTH

TA-L5.1: RECOVERING DEPTH OFA DYNAMIC SCENE USING REAL WORLD 1209

MOTION PRIOR

Adarsh Kowdle, Noah Snavely, Tsuhan Chen, Cornell University, United States

TA-L5.2: SPLIT ANDMERGE APPROACHFOR DETECTING MULTIPLEPLANES IN A .1213

DEPTH IMAGE

Seon-Min Rhee, Yong-Beom Lee, James D. K. Kim, Taehyun Rhee, Samsung Advanced Institute of Technology,Samsung Electronics Co., Republic ofKorea

TA-L5.3: DEPTH ORDERING ON IMAGE SEQUENCES USING MOTION 1217

OCCLUSIONS

Guillem Palou, Philippe Salembier, Technical University ofCatalonia, Spain

TA-L5.4: SDTT-BASED MODELING AND CODING OF BACKGROUND SCENES FOR 1221

MULTIVIEW SOCCER VIDEO

Haopeng Li, Markus Flierl, KTH-Royal Institute of Technology, Sweden

TA-L5.5: FOREGROUND DETECTIONBASED ON LOW-RANKAND BLOCK-SPARSE 1225

MATRIX DECOMPOSITION

Charles Guyon, Thierry Bouwmans, El-Hadi Zahzah, Universite de La Rochelle, France

TA-L5.6: FOREGROUND SDLHOUETTE EXTRACTION ROBUST TO SUDDEN 1229

CHANGES OF BACKGROUND APPEARANCE

Alexandre Alahi, Luigi Bagnato, Damien Matti, Pierre Vandergheynst, Ecole Polytechnique Federate de

Lausanne, Switzerland

TA-L5.7: A STOCHASTIC LEARNINGALGORITHM FORPIXEL-LEVEL BACKGROUND 1233

MODELS

Nick Mould, Joseph Havlicek, University of Oklahoma, United States

TA-P1: BRAIN IMAGING

TA-P1.1: ALTERNATIVE FEATURE EXTRACTION METHODS IN 3D BRAIN 1237

IMAGE-BASED DIAGNOSIS OF ALZHEIMER'S DISEASE

Eduardo Bicacro, Margarida Silveira, Jorge S. Marques, Instituto Superior Tecnico, Portugal

TA-P1.2: FEATURE-BASED BRAIN MRIRETRDEVAL FOR ALZHEIMER DISEASE 1241

DIAGNOSIS

Maxim Mizotin, Lomonosov Moscow State University, France; Jenny Benois-Pineau, University Bordeaux,

LaBRI, France; Michele Allard, Gwenaelle Catheline, University Bordeaux 2, France

TA-P1.3: A FUNCTIONAL CONNECTIVITY INSPIRED APPROACH TO NON-LOCAL 1245

FMRIANALYSIS

Anders Eklund, Linkoping University, Sweden / University ofToronto, Canada; Mats Andersson, Hans

Knutsson, Linkoping University, Sweden

xliii

TA-P1.4: MULTISCALE AND MULTIORD2NTATTON FEATURE EXTRACTION WITH 1249DEGENERATIVE PATTERNS FOR 3D NEUROIMAGING RETRIEVAL

Sidong Liu, Weidong Cai, University ofSydney, Australia; Lingfeng Wen, Royal Prince Alfred Hospital,Australia; David Dagan Feng, University of Sydney, Australia

TA-P1.5: A METHOD FOR DETECTING INTERSTRUCTURAL ATROPHY 1253CORRELATION INMRI BRAIN IMAGESZhuo Sun, Jan.A.C. Veerman, Radu Jasinschi, Philips Research, Netherlands

TA-P1.6: DTIBASED STRUCTURAL DAMAGE CHARACTERIZATION FORDISORDERS 1257OF CONSCIOUSNESS

Francisco Gdmez, Andrea Soddu, Quentin Noirhomme, Audrey Vanhaudenhuyse, Luaba Tshibanda, UniversityofLiege, Belgium; Lepore" Natasha, University ofSouthern California, Belgium; Steven Laureys, University ofLiege, Belgium

TA-P1.7: CONTEXTUAL AND VISUAL MODELINGFOR DETECTION OF MHJ) 1261TRAUMATIC BRAIN INJURY IN MRI

Anthony Bianchi, Bir Bhanu, Virginia Donovan, University ofCalifornia, Riverside, United States; AndreObenaus, Loma Linda University, United States

TA-P1.8: AUTOMATIC DETECTION OF STRUCTURAL CHANGES IN SINGLE 1265CHANNEL LONG TIME-SPAN BRAIN MRIIMAGES USING SALffiNCY MAPANDACTIVE CONTOUR METHODSAndrea Kovacs, Tamas Sziranyi, MTA SZTAKI /PPKEITK, Hungary; Peter Barsi, SOTEMRKK, Hungary

TA-P1.9: A JOINT STRUCTURALAND FUNCTIONAL ANALYSIS OF IN-VITRO 1269NEURONAL NETWORKS

Simona Ullo, Alessio Del Bue, Alessandro Maccione, Luca Berdondini, Vittorio Murino, Istituto Italiano diTecnologia, Italy

TA-P1.10: ROBUST VOXEL-WISE JOINT DETECTIONESTIMATION OF BRAIN 1273ACTIVITY IN FMRI

Lotfi Chaari, Florence Forbes, Thomas Vincent, INRIA Grenoble Rhone-Alpes, UK, France; Philippe Ciuciu,NeuroSpin, CEA Saclay, France

TA-P2: 3D VIDEO & DEPTH CODING

TA-P2.1: TANGENT-PLANE-CONTINUITY MAXIMIZATION BASED 3D POINT 1277COMPRESSION

Wenfei Jiang, Jiang Tian, Kangying Cai, Fan Zhang, Too Luo, Technicolor (China) Technology Co., Ltd.,China

TA-P2.2: DEPTH-ASSISTEDERROR CONCEALMENT FOR INTRA FRAME-SLICES IN 12813D VDDEO

Meng Yang, Xi'anJiaotong University, China; Yuhong Yang, Shanghai Jiaotong University, China; PamelaCosman, University of California, San Diego, United States

TA-P2.3: ADAPTIVENONLOCAL RANGE FILTER INDEPTH MAP CODING 1285Ilsoon Lim, Jaejoon Lee, Samsung Advanced Institute of Technology, Samsung Electronics Co., Republic ofKorea

xliv

TA-P2.4: IMAGE QUALITY VS RATE OPTIMIZED CODING OFWARPS FOR VIEW 1289

SYNTHESIS IN 3D VIDEO APPLICATIONS

Nikolce Stefanoski, Disney Research Zurich, Switzerland; Manuel Lang, Disney Research Zurich/ETH Zurich,

Switzerland; Aljoscha Smolic, Disney Research Zurich, Switzerland

TA-P2.5: EFFICIENT EDGE-PRESERVING INTERPOLATION AND IN-LOOP FILTERS 1293

FOR DEPTH MAP COMPRESSION

VietAnh Nguyen, Dongbo Min, Advanced Digital Sciences Center, Illinois at Singapore, Singapore; Minh N.

Do, University ofIllinois at Urbana-Champaign, UnitedStates

TA-P2.6: DEPTH MAP COMPRESSION USING MULTI-RESOLUTION GRAPH-BASED 1297

TRANSFORM FORDEPTH-IMAGE-BASED RENDERING

Wei Hu, Hong Kong University ofScience and Technology, Hong Kong SAR of China; Gene Cheung, National

Institute ofInformatics, Japan; Xin Li, West Virginia University, United States; Oscar C. Au, Hong KongUniversity ofScience and Technology, Hong Kong SAR of China

TA-P2.7: EDGE-PRESERVING INTERPOLATIONFORDOWN/UPSAMPLING-BASED 1301

DEPTH COMPRESSION

Huiping Deng, Li Yu, Huazhong University ofScience and Technology, China; Zixiang Xiong, Texas A&M

University, United States

TA-P2.8: EFFICHSNT DEPTHMAP CODING USING LINEAR RESIDUE 1305

APPROXIMATIONAND A FLEXD3LE PREDICTIONFRAMEWORK

Luis Lucas, Nuno Rodrigues, Instituto de Telecomunicagdes, Portugal; Carta Pagliari, Instituto Militar de

Engenharia, Brazil; Eduardo Silva, Universidade Federal do Rio de Janeiro, Brazil; Sergio Faria, Instituto de

Telecomunicagdes, Portugal

TA-P2.9: TUNED SPARSE DEPTHMAP CODING USING REDUNDANT PREDEFINED 1309

TRANSFORM DOMAIN

DorsafSebai, Faten Chaieb, Khaled Mamou, Faouzi Ghorbel, University ofManouba, Tunisia

TA-P2.10: DEPTH-BASED WEIGHTED BI-PREDICTION FOR VIDEO PLUS DEPTH 1313

MAP CODING

Shinya Shimizu, Hideaki Kimata, Shiori Sugimoto, Akira Kojima, NTT Corporation, Japan

TA-P2.11: 3D VIDEO COMPRESSIONBY CODING OF DISOCCLUDED REGIONS 1317

Marek Domanski, Jacek Konieczny, Maciej Kurc, Robert Ratajczak, Jakub Siast, Olgierd Stankiewicz, Jakub

Stankowski, KrzysztofWegner, Poznan University ofTechnology, Poland

TA-P2.12: ANALYSIS OFMODE CORRELATIONBETWEEN TEXTURE AND DEPTH 1321

IMAGES IN MULTI-VIEW VIDEO PLUS DEPTH FORMAT

Jin Young Lee, Jaejoon Lee, Du-Sik Park, Samsung Electronics Co., Ltd., Republic ofKorea

TA-P2.13: NEW HEVC PREDICTION MODES FOR3D HOLOSCOPIC VIDEO 1325

CODING

Caroline Conti, Paulo Nunes, Luis Ducla Soares, Instituto de Telecomunicagdes, Portugal

TA-P2.14: JOINTVBEW FILTERING FOR MULTTVD2WDEPTHMAP SEQUENCES 1329

Ri Li, University ofScience and Technology ofChina, China; Dmytro Rusanovskyy, Miska Hannuksela, Nokia

Corp, Finland; Houqiang Li, University ofScience and Technology ofChina, China

xlv

TA-P3: TRACKING II

TA-P3.1: A REGION-BASED PARTICLE FILTERFOR GENERIC OBJECT TRACKING 1333

AND SEGMENTATION

David Varas, Ferran Marques, Universitat Politecnica de Catalunya, Spain

TA-P3.2: PARTIAL MOTION TRAJECTORY GROUPING THROUGHROOTED 1337

ARBORESCENCE

Fan Chen, Japan Advanced Institute ofScience and Technology, Japan; Christophe De Vleeschouwer,

Universite catholique de Louvain, Belgium

TA-P3.3: RAINDROPS SIZE FROM VIDEO AND IMAGE PROCESSING 1341

Michel Desvignes, GIPSA-LAB, France; Gilles Molinii, LTHE, France

TA-P3.4: EVALUATION OF TRACKING ALGORITHM PERFORMANCE WITHOUT 1345

GROUND-TRUTH DATA

Concetto Spampinato, Simone Palazzo, University ofCatania - DIEEI, Italy; Daniela Giordano, University ofCatania, Italy

TA-P3.6: STANDALONE EVALUATION OF DETERMINISTIC VIDEO TRACKING 1353

Juan C. SanMiguel, UniversidadAutdnoma ofMadrid, Spain; Andrea Cavallaro, Queen Mary, University ofLondon, United Kingdom; JosiM. Martinez, UniversidadAutdnoma ofMadrid, Spain

TA-P3.7: JOINT VIEW-IDENTITY MANIFOLDFOR TARGET TRACKING AND .1357

RECOGNITION

Jiulu Gong, Beijing Institute of Technology, China; Guoliang Fan, Liangjiang Yu, Oklahoma State University,United States; Joseph Havlicek, University of Oklahoma, United States; Derong Chen, Beijing Institute ofTechnology, China

TA-P3.8: CAMERA TRACKINGUSING CONCENTRIC CIRCLE MARKERS: PARADIGMS 1361

AND ALGORITHMS

Lilian Calvet, Pierre Gurdjos, Vincent Charvillat, Institut de Recherche en Informatique de Toulouse, France

TA-P3.9: VISUALTRACKINGWITHROBUST TARGETLOCALIZATION..

N/A

Ilker Ersoy, Kannappan Palaniappan, University ofMissouri Columbia, United States; Guna Seetharaman, Air

Force Research Laboratory, United States

TA-P3.10: VARIATIONAL BAYESIAN INFERENCE FORFORWARD-BACKWARD VISUAL ....1369

TRACKING IN STEREO SEQUENCESGiannis Chantas, Nikos Nikolaidis, loannis Pitas, Aristotle University ofThessaloniki, Greece

TA-P4: ACTION RECOGNITION II

TA-P4.1: ACTION RECOGNITION USING INSTANCE-SPECD7IC AND 1373

CLASS-CONSISTENT CUES

Chin-An Lin, National Taiwan University, Taiwan; Yen-Yu Lin, Hong-Yuan MarkLiao, Academia Sinica,

Taiwan; Shyh-Kang Jeng, National Taiwan University, Taiwan

TA-P4.2: MARKOV RANDOM FDELD-BASED REAL-TIME DETECTION OF 1377

INTENTIONALLY-CAPTUREDPERSONS

Tatsuya Koyama, School ofEngineering Osaka University, Japan; Yuta Nakashima, Noboru Babaguchi, Osaka

University, Japan

xlvi

TA-P4.3: HUMAN ACTION CATEGORIES USING MOTION DESCRIPTORS 1381

Xu Zhang, Zhenjiang Miao, Lili Wan, Beijing Jiaotong University, China

TA-P4.4: HUMANACTION RECOGNITION IN VIDEO DATA USING INVARIANT 1385

CHARACTERISTIC VECTORS

NazimAshraf, Hassan Foroosh, University of Central Florida, United States

TA-P4.5: IMPROVED GAITRECOGNITION USING GRADEENTHISTOGRAM ENERGY 1389

IMAGE

Martin Hofinann, Gerhard Rigoll, Technische Universitat Munchen, Germany

TA-P4.6: GAIT RECOGNITION BYLEARNINGDISTRIBUTED KEY POSES 1393

Muhammad Shahzad Cheema, Abdalrahman Eweiwi, University ofBonn, Germany; Christian Bauckhage,

Fraunhofer Institute IAIS, Germany

TA-P4.7: SUPPORT TENSORACTION SPOTTING 1397

Irene Kotsia, Ioannis Patras, Queen Mary, University ofLondon, United Kingdom

TA-P4.8: HUMANACTION CLASSD7ICATION USING SURF BASED SPATIO-TEMPORAL 1401

CORRELATED DESCRD7TORS

Aznul Qalid Md Sabri, Jacques Boonaert, Stephane Lecoeuche, Ecole des Mines de Douai, France; El

Mustapha Mouaddib, Universite de Picardie Jules Verne, France

TA-P4.9: SALBENCY-BASED SELECTION OF SPARSE DESCRIPTORS FOR ACTION 1405

RECOGNITION

Eleonora Vig, Harvard University, United States; Michael Dorr, Harvard Medical School, United States; David

Cox, Harvard University, United States

TA-P4.10: UNSUPERVISED CLASSDJICATION OFEXTREME FACIAL EVENTS USING 1409

ACTIVE APPEARANCEMODELS TRACKINGFOR SIGNLANGUAGE VIDEOS

Epameinondas Antonakos, Vassilis Pitsikalis, Isidoros Rodomagoulakis, Petros Maragos, National Technical

University ofAthens, Greece

TA-P4.11: RECOGNITION WITHRAW CANONICAL PHONETIC MOVEMENTAND 1413

HANDSHAPE SUBUNITS ON VIDEOS OF CONTINUOUS SIGNLANGUAGE

Stavros Theodorakis, Vassilis Pitsikalis, Isidoros Rodomagoulakis, Petros Maragos, National Technical

University ofAthens, Greece

TA-P4.12: RECURRENCE TEXTURES FOR HUMAN ACTIVITY RECOGNITION FROM 1417

COMPRESSIVE CAMERAS

Kuldeep Kulkarni, Pavan Turaga, Arizona State University, United States

TA-P4.13: NON-NEGATIVE SPARSE CODING FOR HUMANACTION RECOGNITION 1421

SeyedMohsen Amiri, Panos Nasiopoulos, Victor CM. Leung, University ofBritish Columbia, Canada

TA-P5: FACE RECOGNITION II

TA-P5.1: INPAINTING OFSPARSE OCCLUSION INFACERECOGNITION 1425

Rui Min, Jean-Luc Dugelay, Eurecom, France

TA-P5.2: FACE RECOGNITION USINGAVERAGEINVARIANT FACTOR 1429

Zhongxuan Luo, Hao Sun, Xin Fan, Jielin Zhang, Dalian University of Technology, China

xlvii

TA-P5.3: SET-BASED LABEL PROPAGATION OF FACE IMAGES 1433

Chao Xiong, Tae-Kyun Kim, Imperial College London, United Kingdom

TA-P5.4: TRANSDUCTIVE VIS-NIRFACE MATCHING 1437

Jun-Yong Zhu, Wei-Shi Zheng, Jianhuang Lai, Sun Yat-Sen University, China

TA-P5.5: PATTERNS OF WEBERMAGNITUDE AND ORIENTATION FOR FACE 1441

RECOGNITION

Biao Wang, Weifeng Li, Tsinghua University, China; Zhimin Li, Shenzhen Municipal Public Security Bureau,

China; Qingmin Liao, Tsinghua University, China

TA-P5.6: A SPARSE REPRESENTATION METHOD WITH MAXIMUM PROBABILITY OF 1445

PARTIAL RANKING FORFACE RECOGNITION

Yi-Haur Shiau, Chaur-Chin Chen, National Tsing Hua University, Taiwan

TA-P5.7: LOCAL LINE DERIVATIVE PATTERN FORFACE RECOGNITION 1449

Zhichao Lian, Meng Joo Er, Nanyang Technological University, Singapore; Yang Cong, Chinese Academy of

Sciences, China

TA-P5.8: MATCHING CROSS-RESOLUTION FACE IMAGES USING CO-TRANSFER 1453

LEARNING

Himanshu Bhatt, Richa Singh, Mayank Vatsa, HIT Delhi, India; Nalini Ratha, IBM T.J. Watson Research

Center, United States

TA-P5.9: PROBABILISTIC FUSIONOF REGIONALSCORES IN 3D FACE 1457

RECOGNITION

Nesli Erdogmus, Lionel Daniel, Jean-Luc Dugelay, Eurecom, France

TA-P5.10: BEST VIEW SELECTIONWITHGEOMETRIC FEATURE BASED FACE 1461

RECOGNITION

Francis Deboeverie, Ghent University, Belgium; Peter Veelaert, University College Ghent, Belgium; Wilfried

Philips, Ghent University, Belgium

TA-P5.11: GRAPH DISCRIMINANT ANALYSIS ONMULTI-MANIFOLD (GDAMM): A 1465

NOVEL SUPER-RESOLUTION METHOD FORFACE RECOGNITION

Junjun Jiang, Ruimin Hu, Zhen Han, Kebin Huang, Tao Lu, Wuhan University, China

TA-P5.12: A SEARCHBASEDAPPROACH TO NON MAXIMUM SUPPRESSION IN FACE 1469

DETECTION

Ekaterina Zaytseva, Jordi Vitria, Computer Vision Center, Universitat de Barcelona, Spain

TA-P6: IMAGE & VIDEO QUALITY

TA-P6.1: SR-SIM: A FAST AND HIGHPERFORMANCE IQA INDEX BASED ON 1473

SPECTRAL RESIDUAL

Lin Zhang, Hongyu Li, Tongji University, China

TA-P6.2: A COMPREHENSIVEEVALUATION OF FULL REFERENCE IMAGE QUALITY .1477

ASSESSMENT ALGORITHMS

Lin Zhang, Tongji University, China; Lei Zhang, Hong Kong Polytechnic University, Hong Kong SAR ofChina;

Xuanqin Mou, XVan Jiaotong University, China; David Zhang, Hong Kong Polytechnic University, Hong KongSAR of China

xlviii

TA-P6.3: OBJECTIVE QUALITYASSESSMENTFOR IMAGE SUPER-RESOLUTION: A 1481

NATURAL SCENE STATISTICS APPROACH

Hojatollah Yeganeh, Mohammad Rostami, Zhou Wang, University of Waterloo, Canada

TA-P6.4: CORRUPTED REFERENCE IMAGE QUALITY ASSESSMENT 1485

Wu Cheng, Keigo Hirakawa, University ofDayton, United States

TA-P6.5: QUALITY ASSESSMENT FOR COLOR IMAGES WITH TUCKER 1489

DECOMPOSITION

Cheng Cheng, Hanli Wang, Tongji University, China

TA-P6.6: A NEW OBJECT BASED QUALITYMETRIC BASED ON SIFT AND SSIM 1493

Marc Decombas, Thales / Telecom ParisTech, France; Frederic Dufaux, Telecom ParisTech, France; Erwann

Renan, Thales, France; Beatrice Pesquet-Popescu, Telecom ParisTech, France; Francois Capman, Thales,

France

TA-P6.7: REDUCED-REFERENCE QUALITY ASSESSMENT FOR RETARGETED 1497

IMAGES

Wenjun Lu, Min Wu, University ofMaryland, College Park, United States

TA-P6.8: A STRATEGY TO JOINTLY TEST IMAGE QUALITYESTIMATORS 1501

SUBJECTIVELY

Amy Reibman, AT&T Labs-Research, United States

TA-P6.9: PERCEPTUAL QUALITY OF VEDEO WITH QUANTIZATION VARIATION : A 1505

SUBJECTIVE STUDY AND ANALYTICAL MODELING

Yen-Fu Ou, Huiqi Zeng, Yao Wang, Polytechnic Institute ofNew York University, United States

TA-P6.10: VIDEO QUALITY METRICBASED ON FIXATION PREDICTION AND 1509

FOVEAL IMAGING

Junyong You, Norwegian University ofScience and Technology, Norway; Touradj Ebrahimi, Swiss Federal

Institute ofTechnology, Lausanne, Switzerland; Andrew Perkis, Norwegian University ofScience and

Technology, Norway

TA-P6.11: OBJECTIVE ASSESSMENT OF THE IMPACT OF FRAME RATE ON VIDEO 1513

QUALITY

Anna Ukhanova, Jari Korhonen, S0ren Forchhammer, Technical University ofDenmark, Denmark

TA-P7: MOTION ESTIMATION & TEMPORAL CODING

TA-P7.1: DECOUPLED COARSE-TO-FINE MATCHINGAND NONLINEAR 1517

REGULARIZATIONFOREFFICIENT MOTION ESTIMATION

Mariano Tepper, Guillermo Sapiro, University ofMinnesota, United States

TA-P7.2: NON-LINEAR OBSERVATIONEQUATIONFORMOTIONESTIMATION 1521

Dominique Bereziat, UPMC, France; Isabelle Herlin, INRIA, France

TA-P7.3: AN OPTIMAL MOTIONVECTOR REGULARIZATION METHOD USING 1525

VARIANCE-DISTORTION CURVE

Hyungjun Lim, DongYoon Kim, Joonsung Choi, Korea Advanced Institute ofScience and Technology (KAIST),

Republic ofKorea; SeungHo Park, Se Hyeok Park, Jae Hyun Kim, Samsung Electronics Co., Ltd., Republic ofKorea; HyunWook Park, Korea Advanced Institute ofScience and Technology (KAIST), Republic ofKorea

xlix

TA-P7.4: HARDWARE-AWARE MOTION ESTIMATION SEARCH ALGORITHM 1529DEVELOPMENT FOR HIGH-EFFKTENCY VIDEO CODING (HEVC) STANDARDMahmut E. Sinangil, Massachusetts Institute of Technology, United States; Vivienne Sze, Minhua Zhou, TexasInstruments Inc., United States; Anantha P. Chandrakasan, Massachusetts Institute ofTechnology, United

States

TA-P7.5: MEMORY COST VS. CODINGEFFICH5NCY TRADE-OFFS FOR HEVC 1533MOTIONESTIMATION ENGINE

Mahmut E. Sinangil, Massachusetts Institute of Technology, United States; Vivienne Sze, Minhua Zhou, Texas

Instruments Inc., United States; Anantha P. Chandrakasan, Massachusetts Institute ofTechnology, UnitedStates

TA-P7.6: A NEWCONSTRUCTION FOR MOTION AND SPEED CAPTUREWITH 1537CONICAL WAVELETS

Patrice Brault, CNRS Centre National de la Recherche Scientifique, France; Jean-Pierre Antoine, Universite

Catholique de Louvain, Belgium

TA-P7.7: ARITHMETIC EDGE CODING FOR ARBITRARILY SHAPED SUB-BLOCK 1541MOTION PREDICTION IN DEPTHVIDEO COMPRESSIONIsmael Daribo, Gene Cheung, National Institute ofInformatics, Japan; Dinei Florencio, Microsoft Research,United States

TA-P7.8: MULTI-DIRECTIONAL IMPLICIT WEIGHTED PREDICTION BASED ON 1545IMAGE CHARACTERISTICS OF REFERENCE PICTURES FORINTER CODING

Akiyuki Tanizawa, Takeshi Chujoh, Tomoo Yamakage, Toshiba Corporation, Japan

TA-P7.9: MOTION VECTOR DERIVATION OF DEFORMABLE BLOCK 1549Na Zhang, Xiaopeng Fan, Debin Zhao, Wen Gao, Harbin Institute of Technology, China

TA-P7.10: QUADTREE-BASED TEMPORAL TRAJECTORY FDLTERING 1553Marko Esche, Alexander Glantz, Andreas Krutz, Michael Tok, Thomas Sikora, Technische Universitat Berlin,Germany