Markerless Motion Capture through Visual Hull, Articulated ICP and Subject Specific Model Generation

An approach for accurately measuring human motion through Markerless Motion Capture (MMC) is presented. The method uses multiple color cameras and combines an accurate and anatomically consistent tracking algorithm with a method for automatically generating subject specific models. The tracking appr...

Full description

Saved in:

Bibliographic Details
Published in:	International journal of computer vision Vol. 87; no. 1-2; pp. 156 - 169
Main Authors:	Corazza, Stefano, Mündermann, Lars, Gambaretto, Emiliano, Ferrigno, Giancarlo, Andriacchi, Thomas P.
Format:	Journal Article
Language:	English
Published:	Boston Springer US 01.03.2010 Springer Springer Nature B.V
Subjects:	Algorithms Analysis Artificial Intelligence Cameras Computer animation Computer Imaging Computer programs Computer Science Datasets Degrees of freedom Image Processing and Computer Vision Mathematical analysis Mathematical models Motion capture Pattern Recognition Pattern Recognition and Graphics Segments Studies Surgical implants Toy industry Tracking Vision Tracking 3D reconstruction Human body model Shape from silhouette Markerless motion capture
ISSN:	0920-5691, 1573-1405
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	An approach for accurately measuring human motion through Markerless Motion Capture (MMC) is presented. The method uses multiple color cameras and combines an accurate and anatomically consistent tracking algorithm with a method for automatically generating subject specific models. The tracking approach employed a Levenberg-Marquardt minimization scheme over an iterative closest point algorithm with six degrees of freedom for each body segment. Anatomical consistency was maintained by enforcing rotational and translational joint range of motion constraints for each specific joint. A subject specific model of the subjects was obtained through an automatic model generation algorithm (Corazza et al. in IEEE Trans. Biomed. Eng., 2009 ) which combines a space of human shapes (Anguelov et al. in Proceedings SIGGRAPH, 2005 ) with biomechanically consistent kinematic models and a pose-shape matching algorithm. There were 15 anatomical body segments and 14 joints, each with six degrees of freedom (13 and 12, respectively for the HumanEva II dataset). The overall method is an improvement over (Mündermann et al. in Proceedings of CVPR, 2007 ) in terms of both accuracy and robustness. Since the method was originally developed for ≥8 cameras, the method performance was tested both (i) on the HumanEva II dataset (Sigal and Black, Technical Report CS-06-08, 2006 ) in a 4 camera configuration, (ii) on a series of motions including walking trials, a very challenging gymnastic motion and a dataset with motions similar to HumanEva II but with variable number of cameras.
AbstractList	An approach for accurately measuring human motion through Markerless Motion Capture (MMC) is presented. The method uses multiple color cameras and combines an accurate and anatomically consistent tracking algorithm with a method for automatically generating subject specific models. The tracking approach employed a Levenberg-Marquardt minimization scheme over an iterative closest point algorithm with six degrees of freedom for each body segment. Anatomical consistency was maintained by enforcing rotational and translational joint range of motion constraints for each specific joint. A subject specific model of the subjects was obtained through an automatic model generation algorithm (Corazza et al. in IEEE Trans. Biomed. Eng., 2009 ) which combines a space of human shapes (Anguelov et al. in Proceedings SIGGRAPH, 2005 ) with biomechanically consistent kinematic models and a pose-shape matching algorithm. There were 15 anatomical body segments and 14 joints, each with six degrees of freedom (13 and 12, respectively for the HumanEva II dataset). The overall method is an improvement over (Mündermann et al. in Proceedings of CVPR, 2007 ) in terms of both accuracy and robustness. Since the method was originally developed for ≥8 cameras, the method performance was tested both (i) on the HumanEva II dataset (Sigal and Black, Technical Report CS-06-08, 2006 ) in a 4 camera configuration, (ii) on a series of motions including walking trials, a very challenging gymnastic motion and a dataset with motions similar to HumanEva II but with variable number of cameras. An approach for accurately measuring human motion through Markerless Motion Capture (MMC) is presented. The method uses multiple color cameras and combines an accurate and anatomically consistent tracking algorithm with a method for automatically generating subject specific models. The tracking approach employed a Levenberg-Marquardt minimization scheme over an iterative closest point algorithm with six degrees of freedom for each body segment. Anatomical consistency was maintained by enforcing rotational and translational joint range of motion constraints for each specific joint. A subject specific model of the subjects was obtained through an automatic model generation algorithm (Corazza et al. in IEEE Trans. Biomed. Eng., 2009) which combines a space of human shapes (Anguelov et al. in Proceedings SIGGRAPH, 2005) with biomechanically consistent kinematic models and a pose-shape matching algorithm. There were 15 anatomical body segments and 14 joints, each with six degrees of freedom (13 and 12, respectively for the HumanEva II dataset). The overall method is an improvement over (Mundermann et al. in Proceedings of CVPR, 2007) in terms of both accuracy and robustness. Since the method was originally developed for [greater than or equal to]8 cameras, the method performance was tested both (i) on the HumanEva II dataset (Sigal and Black, Technical Report CS-06-08, 2006) in a 4 camera configuration, (ii) on a series of motions including walking trials, a very challenging gymnastic motion and a dataset with motions similar to HumanEva II but with variable number of cameras. Keywords Markerless motion capture * Tracking * 3D reconstruction * Human body model * Shape from silhouette An approach for accurately measuring human motion through Markerless Motion Capture (MMC) is presented. The method uses multiple color cameras and combines an accurate and anatomically consistent tracking algorithm with a method for automatically generating subject specific models. The tracking approach employed a Levenberg-Marquardt minimization scheme over an iterative closest point algorithm with six degrees of freedom for each body segment. Anatomical consistency was maintained by enforcing rotational and translational joint range of motion constraints for each specific joint. A subject specific model of the subjects was obtained through an automatic model generation algorithm (Corazza et al. in IEEE Trans. Biomed. Eng., 2009) which combines a space of human shapes (Anguelov et al. in Proceedings SIGGRAPH, 2005) with biomechanically consistent kinematic models and a pose-shape matching algorithm. There were 15 anatomical body segments and 14 joints, each with six degrees of freedom (13 and 12, respectively for the HumanEva II dataset). The overall method is an improvement over (Mundermann et al. in Proceedings of CVPR, 2007) in terms of both accuracy and robustness. Since the method was originally developed for >=8 cameras, the method performance was tested both (i) on the HumanEva II dataset (Sigal and Black, Technical Report CS-06-08, 2006) in a 4 camera configuration, (ii) on a series of motions including walking trials, a very challenging gymnastic motion and a dataset with motions similar to HumanEva II but with variable number of cameras. Issue Title: Special Issue: Evaluation of Articulated Human Motion and Pose Estimation An approach for accurately measuring human motion through Markerless Motion Capture (MMC) is presented. The method uses multiple color cameras and combines an accurate and anatomically consistent tracking algorithm with a method for automatically generating subject specific models. The tracking approach employed a Levenberg-Marquardt minimization scheme over an iterative closest point algorithm with six degrees of freedom for each body segment. Anatomical consistency was maintained by enforcing rotational and translational joint range of motion constraints for each specific joint. A subject specific model of the subjects was obtained through an automatic model generation algorithm (Corazza et al. in IEEE Trans. Biomed. Eng., 2009) which combines a space of human shapes (Anguelov et al. in Proceedings SIGGRAPH, 2005) with biomechanically consistent kinematic models and a pose-shape matching algorithm. There were 15 anatomical body segments and 14 joints, each with six degrees of freedom (13 and 12, respectively for the HumanEva II dataset). The overall method is an improvement over (Mündermann et al. in Proceedings of CVPR, 2007) in terms of both accuracy and robustness. Since the method was originally developed for ≥8 cameras, the method performance was tested both (i) on the HumanEva II dataset (Sigal and Black, Technical Report CS-06-08, 2006) in a 4 camera configuration, (ii) on a series of motions including walking trials, a very challenging gymnastic motion and a dataset with motions similar to HumanEva II but with variable number of cameras.[PUBLICATION ABSTRACT] An approach for accurately measuring human motion through Markerless Motion Capture (MMC) is presented. The method uses multiple color cameras and combines an accurate and anatomically consistent tracking algorithm with a method for automatically generating subject specific models. The tracking approach employed a Levenberg-Marquardt minimization scheme over an iterative closest point algorithm with six degrees of freedom for each body segment. Anatomical consistency was maintained by enforcing rotational and translational joint range of motion constraints for each specific joint. A subject specific model of the subjects was obtained through an automatic model generation algorithm (Corazza et al. in IEEE Trans. Biomed. Eng., 2009) which combines a space of human shapes (Anguelov et al. in Proceedings SIGGRAPH, 2005) with biomechanically consistent kinematic models and a pose-shape matching algorithm. There were 15 anatomical body segments and 14 joints, each with six degrees of freedom (13 and 12, respectively for the HumanEva II dataset). The overall method is an improvement over (Mundermann et al. in Proceedings of CVPR, 2007) in terms of both accuracy and robustness. Since the method was originally developed for [greater than or equal to]8 cameras, the method performance was tested both (i) on the HumanEva II dataset (Sigal and Black, Technical Report CS-06-08, 2006) in a 4 camera configuration, (ii) on a series of motions including walking trials, a very challenging gymnastic motion and a dataset with motions similar to HumanEva II but with variable number of cameras.
Audience	Academic
Author	Andriacchi, Thomas P. Mündermann, Lars Corazza, Stefano Ferrigno, Giancarlo Gambaretto, Emiliano
Author_xml	– sequence: 1 givenname: Stefano surname: Corazza fullname: Corazza, Stefano email: stefanoc@ccrma.stanford.edu organization: Stanford University – sequence: 2 givenname: Lars surname: Mündermann fullname: Mündermann, Lars organization: Stanford University – sequence: 3 givenname: Emiliano surname: Gambaretto fullname: Gambaretto, Emiliano organization: Politecnico di Milano – sequence: 4 givenname: Giancarlo surname: Ferrigno fullname: Ferrigno, Giancarlo organization: Politecnico di Milano – sequence: 5 givenname: Thomas P. surname: Andriacchi fullname: Andriacchi, Thomas P. organization: Stanford University, Bone and Joint RR&D, VA Palo Alto Hospital
BookMark	eNp9kV1rFDEUhoNUcFv9Ad4FvBDBafM1k5nLZantQktLV70NmcyZbdbsZM0H6L8363hhC0ouAuF53pzkPUUnk58AobeUnFNC5EWklDW8IqSrCGtFxV-gBa0lr6gg9QlakI6Rqm46-gqdxrgjpFCML9Bwq8M3CA5ixLc-WT_hlT6kHACnx-Dz9hF_tTFrh6-zcx_xMiRrstMJBrxe3WM9DXiT-x2YhDcHMHa0pgQN4PAVTBD0MfI1ejlqF-HNn_0Mffl0-Xl1Xd3cXa1Xy5vKiFamqqUDkRLGxhjS045qTlknRTOOvamBi4Y1_VDXpu4k77sBGjn0UgATUpuWtoKfofdz7iH47xliUnsbDTinJ_A5qo7IjnPR1oV894zc-RymMpyilPJGSEZYoc5naqsdKDuNPgVtyhpgb00pYLTlfFnwthaEySJ8eCIUJsGPtNU5RrXePDxl5cya4GMMMCpj0-_vKpdYpyhRx2bV3Kwqzapjs4oXkz4zD8Hudfj5X4fNTizstIXw14P_Kf0Ckaq1Sw
CitedBy_id	crossref_primary_10_3389_fbioe_2019_00322 crossref_primary_10_1016_j_cag_2013_10_023 crossref_primary_10_1002_adsr_202200021 crossref_primary_10_1016_j_jbiomech_2014_06_010 crossref_primary_10_1109_JSTSP_2012_2196975 crossref_primary_10_1080_23335432_2021_2003719 crossref_primary_10_1007_s00530_015_0497_y crossref_primary_10_1016_j_patcog_2018_02_013 crossref_primary_10_1109_ACCESS_2024_3485204 crossref_primary_10_1002_hfm_20410 crossref_primary_10_7717_peerj_12995 crossref_primary_10_1007_s11263_011_0451_1 crossref_primary_10_1109_TCSVT_2016_2527218 crossref_primary_10_1097_HP_0000000000000019 crossref_primary_10_1186_s12984_023_01186_9 crossref_primary_10_1007_s11263_015_0832_y crossref_primary_10_1007_s10846_018_0773_0 crossref_primary_10_3390_s24092947 crossref_primary_10_1007_s00138_014_0651_0 crossref_primary_10_1016_j_engappai_2024_109353 crossref_primary_10_1016_j_jbiomech_2011_06_003 crossref_primary_10_3389_fbioe_2020_00181 crossref_primary_10_1109_TIP_2013_2271850 crossref_primary_10_1109_TMM_2012_2189853 crossref_primary_10_1007_s12541_015_0089_y crossref_primary_10_1109_JBHI_2024_3424869 crossref_primary_10_1177_21925682211035083 crossref_primary_10_1080_01691864_2021_1957013 crossref_primary_10_1002_hfm_20840 crossref_primary_10_1016_j_medengphy_2014_07_007 crossref_primary_10_3390_app14114683 crossref_primary_10_3390_s21082836 crossref_primary_10_1007_s11042_017_4847_y crossref_primary_10_1016_j_mio_2016_08_002 crossref_primary_10_1016_j_physio_2023_06_003 crossref_primary_10_1080_14763141_2025_2514234 crossref_primary_10_1109_TCYB_2013_2272321 crossref_primary_10_3390_app15126800 crossref_primary_10_1016_j_ijleo_2015_07_027 crossref_primary_10_3390_s25144400 crossref_primary_10_3390_heritage4040228 crossref_primary_10_3390_s24072338 crossref_primary_10_1007_s10439_011_0418_y crossref_primary_10_1016_j_cviu_2013_07_006 crossref_primary_10_1016_j_imavis_2017_02_002 crossref_primary_10_1016_j_cviu_2011_06_001 crossref_primary_10_1007_s11263_012_0532_9 crossref_primary_10_1109_TPAMI_2013_47 crossref_primary_10_1109_ACCESS_2020_3027260 crossref_primary_10_1109_TPAMI_2017_2740308 crossref_primary_10_5432_jjpehss_015_24089 crossref_primary_10_1109_TIP_2014_2364113 crossref_primary_10_1109_TPAMI_2017_2782743 crossref_primary_10_1115_1_4032878 crossref_primary_10_1016_j_cviu_2011_08_002 crossref_primary_10_3390_s22052010 crossref_primary_10_1109_JSEN_2021_3081188 crossref_primary_10_1109_TBME_2014_2318354 crossref_primary_10_1016_j_humov_2015_08_001 crossref_primary_10_5312_wjo_v12_i7_467 crossref_primary_10_2478_ijcss_2025_0009 crossref_primary_10_1155_2015_186780 crossref_primary_10_1109_TII_2011_2172450 crossref_primary_10_3390_machines11020234 crossref_primary_10_1007_s11263_009_0293_2 crossref_primary_10_3389_fspor_2021_809898 crossref_primary_10_1007_s12283_017_0243_0 crossref_primary_10_3389_fnins_2023_1141567 crossref_primary_10_1111_cgf_12575 crossref_primary_10_1145_3450626_3459792 crossref_primary_10_3390_robotics7040069 crossref_primary_10_1002_adhm_202202987 crossref_primary_10_1080_21681163_2020_1790040 crossref_primary_10_3390_s17071522 crossref_primary_10_2196_19608 crossref_primary_10_3390_machines12010033 crossref_primary_10_1016_j_gaitpost_2024_04_029 crossref_primary_10_1080_21681163_2013_834800 crossref_primary_10_1136_bjsports_2012_091371 crossref_primary_10_3390_s20216258 crossref_primary_10_1007_s11554_018_0825_5 crossref_primary_10_1016_j_measurement_2025_116826 crossref_primary_10_1007_s00138_010_0317_5 crossref_primary_10_1007_s00371_024_03547_4 crossref_primary_10_3389_fnhum_2022_867474 crossref_primary_10_3389_fbioe_2025_1658222 crossref_primary_10_1016_j_imavis_2012_12_001 crossref_primary_10_1016_j_ifacol_2024_09_216 crossref_primary_10_1016_j_imavis_2012_12_003 crossref_primary_10_3390_s22155768 crossref_primary_10_3390_s24092929 crossref_primary_10_1016_j_measurement_2025_117523 crossref_primary_10_3390_s22010051 crossref_primary_10_1186_s40798_018_0139_y crossref_primary_10_1016_j_cviu_2023_103780 crossref_primary_10_1177_1094342014566289 crossref_primary_10_1007_s12283_019_0309_2 crossref_primary_10_14232_analecta_2023_2_24_31 crossref_primary_10_3390_diagnostics15070840 crossref_primary_10_3389_fphys_2024_1407753 crossref_primary_10_1109_TSMC_2017_2664891
Cites_doi	10.1002/cav.43 10.1115/1.2834888 10.1006/cviu.1998.0716 10.1016/j.gaitpost.2004.05.002 10.1117/12.587970 10.1109/34.273735 10.1007/s11263-007-0120-6 10.1109/34.121791 10.1007/s11263-005-4881-5 10.1023/A:1023012723347 10.1016/0734-189X(85)90094-5 10.1023/A:1008071332753 10.1016/j.cviu.2006.08.002 10.1109/TPAMI.2003.1227995 10.1109/34.598236 10.1109/4233.908371 10.1007/s11263-007-0116-2 10.1006/cviu.2001.0918 10.1007/s10439-006-9122-8 10.1016/0262-8856(83)90003-3 10.1016/0262-8856(95)93154-K 10.1006/cviu.1998.0744 10.1111/1467-8659.00392 10.1109/MNRAO.1994.346252 10.1186/1743-0003-3-6 10.1109/CVPR.2007.383340 10.1007/978-3-540-24672-5_15 10.1145/1276377.1276467 10.1109/ICCV.2001.937641 10.1109/TPAMI.1980.6447699 10.1007/11556121_6 10.1109/CVPR.2000.854758 10.1109/CVPR.2007.383302 10.5244/C.19.45 10.1145/1186822.1073207 10.1109/CVPR.1991.139772
ContentType	Journal Article
Copyright	Springer Science+Business Media, LLC 2009 COPYRIGHT 2010 Springer Springer Science+Business Media, LLC 2010
Copyright_xml	– notice: Springer Science+Business Media, LLC 2009 – notice: COPYRIGHT 2010 Springer – notice: Springer Science+Business Media, LLC 2010
DBID	AAYXX CITATION ISR 3V. 7SC 7WY 7WZ 7XB 87Z 8AL 8FD 8FE 8FG 8FK 8FL ABUWG AFKRA ARAPS AZQEC BENPR BEZIV BGLVJ CCPQU DWQXO FRNLG F~G GNUQQ HCIFZ JQ2 K60 K6~ K7- L.- L7M L~C L~D M0C M0N P5Z P62 PHGZM PHGZT PKEHL PQBIZ PQBZA PQEST PQGLB PQQKQ PQUKI PYYUZ Q9U
DOI	10.1007/s11263-009-0284-3
DatabaseName	CrossRef Gale In Context: Science ProQuest Central (Corporate) Computer and Information Systems Abstracts ABI/INFORM Collection ABI/INFORM Global (PDF only) ProQuest Central (purchase pre-March 2016) ABI/INFORM Collection Computing Database (Alumni Edition) Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni) ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central Business Premium Collection ProQuest Technology Collection ProQuest One ProQuest Central Korea Business Premium Collection (Alumni) ABI/INFORM Global (Corporate) ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection Computer Science Database ABI/INFORM Professional Advanced Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ABI/INFORM Global Computing Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Business ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ABI/INFORM Collection China ProQuest Central Basic
DatabaseTitle	CrossRef ABI/INFORM Global (Corporate) ProQuest Business Collection (Alumni Edition) ProQuest One Business Computer Science Database ProQuest Central Student Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ABI/INFORM Complete ProQuest Central ABI/INFORM Professional Advanced ProQuest One Applied & Life Sciences ProQuest Central Korea ProQuest Central (New) Advanced Technologies Database with Aerospace ABI/INFORM Complete (Alumni Edition) Advanced Technologies & Aerospace Collection Business Premium Collection ABI/INFORM Global ProQuest Computing ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition ABI/INFORM China ProQuest Technology Collection ProQuest SciTech Collection ProQuest Business Collection Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition ProQuest One Business (Alumni) ProQuest One Academic ProQuest Central (Alumni) ProQuest One Academic (New) Business Premium Collection (Alumni)
DatabaseTitleList	Computer and Information Systems Abstracts ABI/INFORM Global (Corporate)
Database_xml	– sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Applied Sciences Computer Science
EISSN	1573-1405
EndPage	169
ExternalDocumentID	2793863221 A364854027 10_1007_s11263_009_0284_3
Genre	Feature
GroupedDBID	-4Z -59 -5G -BR -EM -Y2 -~C .4S .86 .DC .VR 06D 0R~ 0VY 199 1N0 1SB 2.D 203 28- 29J 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 3V. 4.4 406 408 409 40D 40E 5GY 5QI 5VS 67Z 6NX 6TJ 78A 7WY 8FE 8FG 8FL 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAOBN AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDBF ABDZT ABECU ABFTD ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACAOD ACBXY ACDTI ACGFO ACGFS ACHSB ACHXU ACIHN ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACREN ACUHS ACZOJ ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADMLS ADRFC ADTPH ADURQ ADYFF ADYOE ADZKW AEAQA AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFGCZ AFKRA AFLOW AFQWF AFWTZ AFYQB AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMTXH AMXSW AMYLF AMYQR AOCGG ARAPS ARCSS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC B-. B0M BA0 BBWZM BDATZ BENPR BEZIV BGLVJ BGNMA BPHCQ BSONS CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 DWQXO EAD EAP EAS EBLON EBS EDO EIOEI EJD EMK EPL ESBYG ESX F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRNLG FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GQ8 GROUPED_ABI_INFORM_COMPLETE GXS H13 HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I-F I09 IAO IHE IJ- IKXTQ ISR ITC ITM IWAJR IXC IZIGR IZQ I~X I~Y I~Z J-C J0Z JBSCW JCJTX JZLTJ K60 K6V K6~ K7- KDC KOV KOW LAK LLZTM M0C M0N M4Y MA- N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P19 P2P P62 P9O PF0 PQBIZ PQBZA PQQKQ PROAC PT4 PT5 QF4 QM1 QN7 QO4 QOK QOS R4E R89 R9I RHV RNI RNS ROL RPX RSV RZC RZE RZK S16 S1Z S26 S27 S28 S3B SAP SCJ SCLPG SCO SDH SDM SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TAE TEORI TSG TSK TSV TUC TUS U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 Z7R Z7S Z7V Z7W Z7X Z7Y Z7Z Z83 Z86 Z88 Z8M Z8N Z8P Z8Q Z8R Z8S Z8T Z8W Z92 ZMTXR ~8M ~EX AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC ADHKG ADKFA AEZWR AFDZB AFFHD AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION ICD PHGZM PHGZT PQGLB 7SC 7XB 8AL 8FD 8FK JQ2 L.- L7M L~C L~D PKEHL PQEST PQUKI Q9U
ID	FETCH-LOGICAL-c487t-81d077ef6cc0b191a3129746ffbc5e34626bd55c5973b9de67db74e247ac81843
IEDL.DBID	RSV
ISICitedReferencesCount	138
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000273242300009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0920-5691
IngestDate	Wed Oct 01 14:16:30 EDT 2025 Tue Nov 04 19:45:18 EST 2025 Sat Nov 29 09:51:27 EST 2025 Wed Nov 26 10:06:59 EST 2025 Tue Nov 18 22:36:00 EST 2025 Sat Nov 29 06:42:24 EST 2025 Fri Feb 21 02:26:39 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	1-2
Keywords	Tracking 3D reconstruction Human body model Shape from silhouette Markerless motion capture
Language	English
License	http://www.springer.com/tdm
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c487t-81d077ef6cc0b191a3129746ffbc5e34626bd55c5973b9de67db74e247ac81843
Notes	SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23
PQID	1113647202
PQPubID	1456341
PageCount	14
ParticipantIDs	proquest_miscellaneous_907933485 proquest_journals_1113647202 gale_infotracacademiconefile_A364854027 gale_incontextgauss_ISR_A364854027 crossref_citationtrail_10_1007_s11263_009_0284_3 crossref_primary_10_1007_s11263_009_0284_3 springer_journals_10_1007_s11263_009_0284_3
PublicationCentury	2000
PublicationDate	2010-03-01
PublicationDateYYYYMMDD	2010-03-01
PublicationDate_xml	– month: 03 year: 2010 text: 2010-03-01 day: 01
PublicationDecade	2010
PublicationPlace	Boston
PublicationPlace_xml	– name: Boston – name: New York
PublicationTitle	International journal of computer vision
PublicationTitleAbbrev	Int J Comput Vis
PublicationYear	2010
Publisher	Springer US Springer Springer Nature B.V
Publisher_xml	– name: Springer US – name: Springer – name: Springer Nature B.V
References	Plankers, Fua (CR43) 2003; 25 Besl, McKay (CR7) 1992; 14 Aggarwal, Cai (CR1) 1999; 73 Rosenhahn, Brox, Kersting, Smith, Gurney, Klette (CR45) 2006; 1 CR39 CR38 CR37 CR35 CR31 Corazza, Mündermann, Chaudhari, Demattio, Cobelli, Andriacchi (CR13) 2006; 34 O’Rourke, Badler (CR42) 1980; 2 Moeslund, Hilton, Krüger (CR34) 2006; 104 Hogg (CR20) 1983; 1 Wren, Azarbayejani, Darrell, Pentland (CR48) 1997; 19 Mündermann, Corazza, Chaudhari, Alexander, Andriacchi (CR36) 2005; 5665 CR4 CR3 Marzani, Calais, Legrand (CR32) 2001; 5 CR6 CR5 CR8 CR49 CR46 Knossow, Ronfard, Horaud (CR24) 2008; 79 Kohli, Rihan, Bray, Torr (CR25) 2008; 79 CR44 CR41 CR40 Wagg, Nixon (CR47) 2004; 15 Kakadiaris, Metaxas (CR22) 1998; 30 Andriacchi, Alexander, Toney, Dyrby, Sum (CR2) 1998; 120 Laurentini (CR26) 1994; 16 Mikic, Trivedi, Hunter, Cosman (CR33) 2003; 53 CR19 CR17 CR16 CR15 Gavrila (CR18) 1999; 73 CR14 CR10 Leardini, Chiari, Della Croce, Cappozzo (CR27) 2005; 21 Legrand, Marzani, Dusserre (CR30) 1998; 9 Cheung, Baker, Kanade (CR12) 2005; 62 Bottino, Laurentini (CR9) 2001; 83 CR29 Lee, Chen (CR28) 1985; 30 CR23 CR21 Cedras, Shah (CR11) 1995; 13 K. Cheung (284_CR12) 2005; 62 284_CR29 T. P. Andriacchi (284_CR2) 1998; 120 L. Legrand (284_CR30) 1998; 9 A. Laurentini (284_CR26) 1994; 16 284_CR23 P. Besl (284_CR7) 1992; 14 284_CR31 284_CR8 284_CR6 284_CR5 T. B. Moeslund (284_CR34) 2006; 104 284_CR4 284_CR3 J. Aggarwal (284_CR1) 1999; 73 284_CR19 284_CR17 284_CR15 284_CR16 284_CR14 284_CR21 I. Mikic (284_CR33) 2003; 53 S. Corazza (284_CR13) 2006; 34 R. Plankers (284_CR43) 2003; 25 L. Mündermann (284_CR36) 2005; 5665 J. O’Rourke (284_CR42) 1980; 2 B. Rosenhahn (284_CR45) 2006; 1 D. K. Wagg (284_CR47) 2004; 15 F. Marzani (284_CR32) 2001; 5 H. J. Lee (284_CR28) 1985; 30 D. Knossow (284_CR24) 2008; 79 284_CR49 284_CR46 284_CR44 284_CR10 P. Kohli (284_CR25) 2008; 79 I. A. Kakadiaris (284_CR22) 1998; 30 C. R. Wren (284_CR48) 1997; 19 A. Bottino (284_CR9) 2001; 83 D. Gavrila (284_CR18) 1999; 73 284_CR39 284_CR37 284_CR38 284_CR35 C. Cedras (284_CR11) 1995; 13 D. Hogg (284_CR20) 1983; 1 284_CR40 284_CR41 A. Leardini (284_CR27) 2005; 21
References_xml	– volume: 15 start-page: 399 year: 2004 end-page: 406 ident: CR47 article-title: Automated markerless extraction of walking people using deformable contour models publication-title: Computer Animation and Virtual Worlds doi: 10.1002/cav.43 – ident: CR49 – ident: CR4 – ident: CR39 – ident: CR16 – volume: 120 start-page: 743 year: 1998 end-page: 749 ident: CR2 article-title: A point cluster method for in vivo motion analysis: applied to a study of knee kinematics publication-title: Journal of Biomechanical Engineering doi: 10.1115/1.2834888 – ident: CR35 – ident: CR29 – volume: 73 start-page: 82 issue: 3 year: 1999 end-page: 98 ident: CR18 article-title: The visual analysis of human movement: a survey publication-title: Computer Vision and Image Understanding doi: 10.1006/cviu.1998.0716 – ident: CR8 – volume: 21 start-page: 221 year: 2005 end-page: 225 ident: CR27 article-title: Human movement analysis using stereophotogrammetry. Part 3: Soft tissue artifact assessment and compensation publication-title: Gait and Posture doi: 10.1016/j.gaitpost.2004.05.002 – ident: CR21 – ident: CR46 – ident: CR19 – ident: CR15 – volume: 5665 start-page: 278 year: 2005 end-page: 287 ident: CR36 article-title: Most favorable camera configuration for a shape-from-silhouette markerless motion capture system for biomechanical analysis publication-title: Proceedings of SPIE-IS&T Electronic Imaging doi: 10.1117/12.587970 – volume: 16 start-page: 150 year: 1994 end-page: 162 ident: CR26 article-title: The Visual Hull concept for silhouette base image understanding publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.273735 – volume: 79 start-page: 285 issue: 3 year: 2008 end-page: 298 ident: CR25 article-title: Simultaneous segmentation and pose estimation of humans using dynamic graph cuts publication-title: International Journal of Computer Vision doi: 10.1007/s11263-007-0120-6 – volume: 14 start-page: 239 issue: 2 year: 1992 end-page: 256 ident: CR7 article-title: A method for registration of 3D shapes publication-title: Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.121791 – ident: CR5 – volume: 62 start-page: 221 year: 2005 end-page: 247 ident: CR12 article-title: Shape-from-silhouette across time part I: Theory and algorithm publication-title: International Journal of Computer Vision doi: 10.1007/s11263-005-4881-5 – volume: 1 start-page: 45 year: 2006 end-page: 51 ident: CR45 article-title: A system for marker-less motion capture publication-title: Künstliche Intelligenz (KI) – volume: 53 start-page: 199 year: 2003 end-page: 223 ident: CR33 article-title: Human body model acquisition and tracking using voxel data publication-title: International Journal of Computer Vision doi: 10.1023/A:1023012723347 – volume: 30 start-page: 148 year: 1985 end-page: 168 ident: CR28 article-title: Determination of 3D human body posture from a single view publication-title: Computer Vision, Graphics, and Image Processing doi: 10.1016/0734-189X(85)90094-5 – volume: 30 start-page: 191 year: 1998 ident: CR22 article-title: Three-dimensional human body model acquisition from multiple views publication-title: International Journal of Computer Vision doi: 10.1023/A:1008071332753 – volume: 104 start-page: 90 issue: 2 year: 2006 end-page: 126 ident: CR34 article-title: A survey of advances in vision-based human motion capture and analysis publication-title: Computer Vision and Image Understanding doi: 10.1016/j.cviu.2006.08.002 – ident: CR14 – volume: 25 start-page: 1182 year: 2003 end-page: 1187 ident: CR43 article-title: Articulated soft objects for multiview shape and motion capture publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/TPAMI.2003.1227995 – ident: CR37 – volume: 19 start-page: 780 year: 1997 end-page: 785 ident: CR48 article-title: Pfinder—real-time tracking of the human body publication-title: Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.598236 – volume: 5 start-page: 18 issue: 1 year: 2001 end-page: 26 ident: CR32 article-title: A 3-D marker-free system for the analysis of movement disabilities—an application to the legs publication-title: IEEE Transactions on Information Technology in Biomedicine doi: 10.1109/4233.908371 – ident: CR10 – ident: CR6 – ident: CR40 – volume: 79 start-page: 247 issue: 2 year: 2008 end-page: 269 ident: CR24 article-title: Human motion tracking with a kinematic parameterization of extremal contours publication-title: International Journal of Computer Vision doi: 10.1007/s11263-007-0116-2 – volume: 83 start-page: 79 year: 2001 ident: CR9 article-title: A silhouette based technique for the reconstruction of human movement publication-title: Computer Vision and Image Understanding doi: 10.1006/cviu.2001.0918 – ident: CR23 – volume: 34 start-page: 1019 issue: 6 year: 2006 end-page: 1029 ident: CR13 article-title: A markerless motion capture system to study musculoskeletal biomechanics: visual hull and simulated annealing approach publication-title: Annals Biomedical Engineering doi: 10.1007/s10439-006-9122-8 – ident: CR44 – volume: 1 start-page: 5 year: 1983 ident: CR20 article-title: Model-based vision: a program to see a walking person publication-title: Image and Vision Computing doi: 10.1016/0262-8856(83)90003-3 – ident: CR3 – ident: CR38 – ident: CR17 – ident: CR31 – volume: 13 start-page: 129 issue: 2 year: 1995 end-page: 155 ident: CR11 article-title: Motion-based recognition: a survey publication-title: Image and Vision Computing doi: 10.1016/0262-8856(95)93154-K – volume: 9 start-page: 1066 year: 1998 end-page: 1070 ident: CR30 article-title: A marker-free system for the analysis of. movement disabilities publication-title: Medinfo – ident: CR41 – volume: 73 start-page: 295 issue: 3 year: 1999 end-page: 304 ident: CR1 article-title: Human motion analysis: a review publication-title: Computer Vision and Image Understanding doi: 10.1006/cviu.1998.0744 – volume: 2 start-page: 522 year: 1980 end-page: 536 ident: CR42 article-title: Model-based image analysis of human motion using constraint propagation publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence – ident: 284_CR29 doi: 10.1111/1467-8659.00392 – volume: 79 start-page: 285 issue: 3 year: 2008 ident: 284_CR25 publication-title: International Journal of Computer Vision doi: 10.1007/s11263-007-0120-6 – ident: 284_CR8 doi: 10.1109/MNRAO.1994.346252 – volume: 15 start-page: 399 year: 2004 ident: 284_CR47 publication-title: Computer Animation and Virtual Worlds doi: 10.1002/cav.43 – volume: 62 start-page: 221 year: 2005 ident: 284_CR12 publication-title: International Journal of Computer Vision doi: 10.1007/s11263-005-4881-5 – ident: 284_CR37 doi: 10.1186/1743-0003-3-6 – ident: 284_CR40 – volume: 34 start-page: 1019 issue: 6 year: 2006 ident: 284_CR13 publication-title: Annals Biomedical Engineering doi: 10.1007/s10439-006-9122-8 – volume: 1 start-page: 45 year: 2006 ident: 284_CR45 publication-title: Künstliche Intelligenz (KI) – ident: 284_CR5 doi: 10.1109/CVPR.2007.383340 – volume: 5 start-page: 18 issue: 1 year: 2001 ident: 284_CR32 publication-title: IEEE Transactions on Information Technology in Biomedicine doi: 10.1109/4233.908371 – ident: 284_CR16 doi: 10.1007/978-3-540-24672-5_15 – volume: 120 start-page: 743 year: 1998 ident: 284_CR2 publication-title: Journal of Biomechanical Engineering doi: 10.1115/1.2834888 – ident: 284_CR19 – ident: 284_CR15 – volume: 79 start-page: 247 issue: 2 year: 2008 ident: 284_CR24 publication-title: International Journal of Computer Vision doi: 10.1007/s11263-007-0116-2 – volume: 16 start-page: 150 year: 1994 ident: 284_CR26 publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.273735 – ident: 284_CR6 doi: 10.1145/1276377.1276467 – volume: 30 start-page: 148 year: 1985 ident: 284_CR28 publication-title: Computer Vision, Graphics, and Image Processing doi: 10.1016/0734-189X(85)90094-5 – volume: 5665 start-page: 278 year: 2005 ident: 284_CR36 publication-title: Proceedings of SPIE-IS&T Electronic Imaging – ident: 284_CR23 – volume: 73 start-page: 295 issue: 3 year: 1999 ident: 284_CR1 publication-title: Computer Vision and Image Understanding doi: 10.1006/cviu.1998.0744 – volume: 30 start-page: 191 year: 1998 ident: 284_CR22 publication-title: International Journal of Computer Vision doi: 10.1023/A:1008071332753 – ident: 284_CR35 doi: 10.1109/ICCV.2001.937641 – volume: 2 start-page: 522 year: 1980 ident: 284_CR42 publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/TPAMI.1980.6447699 – volume: 53 start-page: 199 year: 2003 ident: 284_CR33 publication-title: International Journal of Computer Vision doi: 10.1023/A:1023012723347 – ident: 284_CR44 doi: 10.1007/11556121_6 – ident: 284_CR3 – volume: 19 start-page: 780 year: 1997 ident: 284_CR48 publication-title: Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.598236 – volume: 21 start-page: 221 year: 2005 ident: 284_CR27 publication-title: Gait and Posture doi: 10.1016/j.gaitpost.2004.05.002 – volume: 14 start-page: 239 issue: 2 year: 1992 ident: 284_CR7 publication-title: Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.121791 – volume: 83 start-page: 79 year: 2001 ident: 284_CR9 publication-title: Computer Vision and Image Understanding doi: 10.1006/cviu.2001.0918 – ident: 284_CR17 doi: 10.1109/CVPR.2000.854758 – volume: 73 start-page: 82 issue: 3 year: 1999 ident: 284_CR18 publication-title: Computer Vision and Image Understanding doi: 10.1006/cviu.1998.0716 – volume: 104 start-page: 90 issue: 2 year: 2006 ident: 284_CR34 publication-title: Computer Vision and Image Understanding doi: 10.1016/j.cviu.2006.08.002 – ident: 284_CR38 doi: 10.1109/CVPR.2007.383302 – volume: 9 start-page: 1066 year: 1998 ident: 284_CR30 publication-title: Medinfo – volume: 25 start-page: 1182 year: 2003 ident: 284_CR43 publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/TPAMI.2003.1227995 – ident: 284_CR41 doi: 10.5244/C.19.45 – ident: 284_CR46 – ident: 284_CR21 – ident: 284_CR4 doi: 10.1145/1186822.1073207 – ident: 284_CR39 – ident: 284_CR49 doi: 10.1109/CVPR.1991.139772 – volume: 13 start-page: 129 issue: 2 year: 1995 ident: 284_CR11 publication-title: Image and Vision Computing doi: 10.1016/0262-8856(95)93154-K – volume: 1 start-page: 5 year: 1983 ident: 284_CR20 publication-title: Image and Vision Computing doi: 10.1016/0262-8856(83)90003-3 – ident: 284_CR10 – ident: 284_CR14 – ident: 284_CR31
SSID	ssj0002823
Score	2.3677104
Snippet	An approach for accurately measuring human motion through Markerless Motion Capture (MMC) is presented. The method uses multiple color cameras and combines an... Issue Title: Special Issue: Evaluation of Articulated Human Motion and Pose Estimation An approach for accurately measuring human motion through Markerless...
SourceID	proquest gale crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	156
SubjectTerms	Algorithms Analysis Artificial Intelligence Cameras Computer animation Computer Imaging Computer programs Computer Science Datasets Degrees of freedom Image Processing and Computer Vision Mathematical analysis Mathematical models Motion capture Pattern Recognition Pattern Recognition and Graphics Segments Studies Surgical implants Toy industry Tracking Vision
SummonAdditionalLinks	– databaseName: ABI/INFORM Global dbid: M0C link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3fa9swED66tA97adp1Y97SIcpgsM3MsWwrfiolLLQPCaXdSt-EJMsjEJw0ivf3786W0x9jfdmLH2z5JHPS-T7d6T6Aj6oUqGceh1rhckPEYMNRpjK8oGWMdMaViRqyCTGbjW5v80u_4eZ8WmVnExtDXSwN7ZF_I0p0KnUexaeru5BYoyi66ik0XsAueTaU0jeNxltLjHCipZJHiJRm-bCLajZH54YxRTApNIAWOuSP_ktPrfNfYdLm7zPp_--4D2Df-53srJ0oh7Bjq1fQ9z4o8yvc4a2O5qG7dwQFneexFJR3bNqQ_rCxWlHkgXmWH3YzdzVKP0c8-7Xtg1jBUPDF-JKpCjuoNW34sIbuvpwbRhxsC9YWvSaRr-Hn5PuP8XnoyRlCgxhnE6KfGwlhy8yYSCPoUxw9B5FkZalNanmCQEkXaWoQsHCdFzYThRaJjROhzIhIZt5Ar1pW9i0wI1IxVAKdhVIk6LDluuQItGKbKIPwbBhA1KlGGl-5nAg0FvK-5jJpU6I2JWlT8gA-b19ZtWU7nmt8QvqWVA6jonybX6p2Tl5cX8kz1N0IndpYBPDJNyqX2LlR_vgCfgJV0HrUctDNBOkNgpP30yAAtn2MS5niM6qyy9rJnIoVcpQSwJduuj2Q8K_hv3u-v_fwss14oLy5AfQ269oew575vZm79YdmwfwB0DAXrA priority: 102 providerName: ProQuest
Title	Markerless Motion Capture through Visual Hull, Articulated ICP and Subject Specific Model Generation
URI	https://link.springer.com/article/10.1007/s11263-009-0284-3 https://www.proquest.com/docview/1113647202 https://www.proquest.com/docview/907933485
Volume	87
WOSCitedRecordID	wos000273242300009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVPQU databaseName: ABI/INFORM Collection customDbUrl: eissn: 1573-1405 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002823 issn: 0920-5691 databaseCode: 7WY dateStart: 19970101 isFulltext: true titleUrlDefault: https://www.proquest.com/abicomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ABI/INFORM Global customDbUrl: eissn: 1573-1405 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002823 issn: 0920-5691 databaseCode: M0C dateStart: 19970101 isFulltext: true titleUrlDefault: https://search.proquest.com/abiglobal providerName: ProQuest – providerCode: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 1573-1405 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002823 issn: 0920-5691 databaseCode: P5Z dateStart: 19970101 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: Computer Science Database customDbUrl: eissn: 1573-1405 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002823 issn: 0920-5691 databaseCode: K7- dateStart: 19970101 isFulltext: true titleUrlDefault: http://search.proquest.com/compscijour providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1573-1405 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002823 issn: 0920-5691 databaseCode: BENPR dateStart: 19970101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1573-1405 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002823 issn: 0920-5691 databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3da9swED_6sYe9rGu3Um9dEKMwWGdwLNuyH7vQ0jIaQrr160VIilwCwSlVvL9_d7acrltX6F4EduSTI-lO9_NJ9wPYU6XAceZxqBWqGyIGG-aZyrBAyxjpjCsTNWQTYjjMLy-LkT_H7brd7l1IsrHU94fd-jHFHOljPtrUkK_COq52OfE1jM_Ol-YXMUTLH4-4KM2KfhfKfEzEg8XoT5P8V2y0WXKONv7rZV_DK-9hsoN2SmzCiq22YMN7m8zrssNbHaFDd-8NTOjkjqXwu2OnDb0PG6hbijEwz-fDzqeuRunHiFy_tG0Q_xcKPhmMmKqwgVrTpx3WENuXU8OIbW3G2vTWJPIt_Dg6_D44Dj0NQ2gQzSxC9GgjIWyZGRNphHeKo48gkqwstUktTxAS6UmaGoQmXBcTm4mJFomNE6FMTnQy27BWzSu7A8yIVPSVQLegFAm6ZoUuOUKq2CbKIBDrBxB14yGNz1FOVBkzeZ9dmTpWYsdK6ljJA_i8fOS2TdDxVOWPNMiSEl9UtLPmRtXOyZOzsTzgWZKj-xqLAD75SuUcGzfKH1TAv0C5sh7U3O0mi_Sq7whSNTn5ozgAtvwZlZYiMaqy89rJgtIScpQSwH43f36T8K_Xf_es2u_hZbvVgTbM7cLa4q62H-CF-bmYurserIqLqx6sfz0cjsZ49U2EWJ5GAyxH6XWvUapfuNISrA
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6VggQXyqsiUMBCICQgajZO4uSAULVQ7WrbVUUL6s3YjoMqVdml3oD4U_2NnUmcLQXRWw9c9pB1xnl8nkdmPB_AC1UJfM88DrXC5YYRgw3zTGX4g5ox0hlXJmrJJsR0mh8eFnsrcNrvhaGyyl4ntoq6nBn6Rr5JlOjU6jyK38-_h8QaRdnVnkKjg8XE_vqJIZt7N_6A7_dlHG9_PBiOQs8qEBp0zhchOmiRELbKjIk0RiuKo8kTSVZV2qSWJ-jh6zJNDXraXBelzUSpRWLjRCiTEzsKyr0G1xOeC1pXExEuNT-GLx11PYZkaVYM-ixqu1VvEFPGlFIRaBFCfsEO_mkN_krLttZue-1_e0534Lb3q9lWtxDuwoqt78Ga97GZ12AOD_U0Fv2x-1DSfiVLRQeO7bakRmyo5pRZYZ7FiH05cg1KH2G8_rabg1jPUPB4uMdUjRM0mj5osf25bYscGXHMHbOuqTeJfACfr-T212G1ntX2ITAjUjFQAp2hSiTokBa64hhIxjZRBsPPQQBRDwVpfGd2Igg5luc9pQk9EtEjCT2SB_B6ecq8a0ty2eDnhC9J7T5qqif6phrn5Hj_k9xCrOTotMcigFd-UDXDyY3y2zPwFqhD2IWRGz3ypFd4Tp7DLgC2_BtVFeWfVG1njZMFNWPkKCWANz28f5Pwr8t_dPl8z-Dm6GB3R-6Mp5PHcKur7qAawQ1YXZw09gncMD8WR-7kabtYGXy9atSfAYQgc-4
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3db9MwED-NgRAvjE8RGGAhEBIQLY2TuHlAaOqoVg2qigGaeDG246BJU1rmBsS_xl_HXWJ3DMTe9sBLH1LnXDc_30fufD-Ax6oW-Jx5GmuF2w0jBhsPC1XgB2rGRBdcmaQjmxDT6fDgoJytwc9wFobKKoNO7BR1NTf0jnyLKNGp1XmSbtW-LGK2M361-BoTgxRlWgOdRg-RPfvjO4Zv7uVkB5_1kzQdv34_2o09w0Bs0FFfxuisJULYujAm0Ri5KI7mT2RFXWuTW56ht6-rPDfodXNdVrYQlRaZTTOhzJCYUlDuBbiId5RUTjjLP62sAIYyPY09hmd5UQ5CRrU7tjdIKXtKaQm0DjE_ZRP_tAx_pWg7yzfe-J__s2tw1fvbbLvfINdhzTY3YMP73sxrNoeXAr1FuHYTKjrHZKkYwbG3HdkRG6kFZVyYZzdiHw9di9J3cdkv-jmIDQ0FT0YzphqcoNX0oovtL2xX_MiIe-6I9c2-SeQt-HAuy78N6828sXeAGZGLgRLoJNUiQ0e11DXHADO1mTIYlg4iSAIspPEd24k45Eie9JomJElEkiQkSR7Bs9Uti75dyVmDHxHWJLUBaQgcX1TrnJzsv5PbiJshOvOpiOCpH1TPcXKj_LENXAJ1Djs1cjOgUHpF6OQJBCNgq69RhVFeSjV23jpZUpNGjlIieB6g_puEf_38u2fP9xAuI9jlm8l07x5c6Ys-qHRwE9aXx629D5fMt-WhO37Q7VsGn88b9L8AgZZ9Eg
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Markerless+Motion+Capture+through+Visual+Hull%2C+Articulated+ICP+and+Subject+Specific+Model+Generation&rft.jtitle=International+journal+of+computer+vision&rft.au=Corazza%2C+Stefano&rft.au=M%C3%BCndermann%2C+Lars&rft.au=Gambaretto%2C+Emiliano&rft.au=Ferrigno%2C+Giancarlo&rft.date=2010-03-01&rft.pub=Springer+US&rft.issn=0920-5691&rft.eissn=1573-1405&rft.volume=87&rft.issue=1-2&rft_id=info:doi/10.1007%2Fs11263-009-0284-3&rft.externalDocID=10_1007_s11263_009_0284_3
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0920-5691&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0920-5691&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0920-5691&client=summon