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We address the problem of making human motion capture in the wild more practical by using a small set of inertial sensors attached to the body.
A mathematical introduction to robotic manipulation
Murray R. M., Li Z., Sastry S. S., Sastry S. S · 1994
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Performance animation from low-dimensional control signals
Chai J., Hodgins J. K · 2005
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Moven: Full 6dof human motion tracking using miniature inertial sensors
Roetenberg D., Luinge H., Slycke P · 2007
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Action capture with accelerometers
Slyper R., Hodgins J · 2008
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Articulated mesh animation from multi-view silhouettes
Vlasic D., Baran I., Matusik W., Popović J · 2008
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Motion capture using joint skeleton tracking and surface estimation
Gall J., Stoll C., De Aguiar E., Theobalt C., Rosenhahn B., Seidel H.-P · 2009
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Ball joints for marker-less human motion capture
Pons-Moll G., Rosenhahn B · 2009
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Discriminative human full-body pose estimation from wearable inertial sensor data
Schwarz L., Mateus D., Navab N · 2009
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Analyzing and evaluating markerless motion tracking using inertial sensors
Baak A., Helten T., Müller M., Pons-Moll G., Rosenhahn B., Seidel H.-P · 2010
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Humaneva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion
Sigal L., Balan A., Black M · 2010
Cited alongside, same era.
Realtime human motion control with a small number of inertial sensors
Liu H., Wei X., Chai J., Ha I., Rhee T · 2011
Cited alongside, same era.
Model-Based Pose Estimation
Pons-Moll G., Rosenhahn B · 2011
Cited alongside, same era.
Motion capture from body-mounted cameras
Shiratori T., Park H. S., Sigal L., Sheikh Y., Hodgins J. K · 2011
Cited alongside, same era.
Motion reconstruction using sparse accelerometer data
Tautges J., Zinke A., Krüger B., Baumann J., Weber A., Helten T., Müller M., Seidel H.-P., Eberhardt B · 2011
Cited alongside, same era.
Real-time body tracking with one depth camera and inertial sensors
Helten T., Muller M., Seidel H.-P., Theobalt C · 2013
SMPL: A skinned multi-person linear model
Loper M., Mahmood N., Romero J., Pons-Moll G., Black M. J · 2015
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Dyna: A model of dynamic human shape in motion
Pons-Moll G., Romero J., Mahmood N., Black M. J · 2015
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Robust articulated-ICP for real-time hand tracking
Tagliasacchi A., Schröder M., Tkach A., Bouaziz S., Botsch M., Pauly M · 2015
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Real-time physics-based motion capture with sparse sensors
Andrews S., Huerta I., Komura T., Sigal L., Mitchell K · 2016
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Keep it SMPL: Automatic estimation of 3D human pose and shape from a single image
Bogo F., Kanazawa A., Lassner C., Gehler P., Romero J., Black M. J · 2016
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Sensor-based gait parameter extraction with deep convolutional neural networks
Hannink J., Kautz T., Pasluosta C., Gassmann K.-G., Klucken J., Eskofier B · 2016
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Cited alongside, same era.
Rotation averaging
Hartley R., Trumpf J., Dai Y., Li H · 2013
Cited alongside, same era.
Human3.6M: Large scale datasets and predictive methods for 3D human sensing in natural environments
Ionescu C., Papava D., Olaru V., Sminchisescu C · 2014
Cited alongside, same era.
Pose-conditioned joint angle limits for 3D human pose reconstruction
Akhter I., Black M. J · 2015
Cited alongside, same era.
http://mocap.cs.cmu.edu/
CMU motion capture database
Cited in the paper.
http://www.mixamo.com/
Mixamo
Cited in the paper.
http://moves.com/
House of moves
Cited in the paper.
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Human pose estimation from video and IMUs
Marcard T. v., Pons-Moll G., Rosenhahn B · 2016
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Body Talk: Crowdshaping realistic 3D avatars with words
Streuber S., Quiros-Ramirez M. A., Hill M. Q., Hahn C. A., Zuffi S., O’Toole A., Black M. J · 2016
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Efficient and precise interactive hand tracking through joint, continuous optimization of pose and correspondences
Taylor J., Bordeaux L., Cashman T., Corish B., Keskin C., Sharp T., Soto E., Sweeney D., Valentin J., Luff B., et al · 2016
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