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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
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