From Image to Stability: Learning Dynamics from Human Pose

[1]  Cordelia Schmid,et al.  LCR-Net++: Multi-Person 2D and 3D Pose Detection in Natural Images , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Gunnar Blohm,et al.  Movement science needs different pose tracking algorithms , 2019, ArXiv.

[3]  Thomas Brox,et al.  What Do Single-View 3D Reconstruction Networks Learn? , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[4]  Nicolas Mansard,et al.  Estimating 3D Motion and Forces of Person-Object Interactions From Monocular Video , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Dong Liu,et al.  Deep High-Resolution Representation Learning for Human Pose Estimation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Frédo Durand,et al.  What Do Different Evaluation Metrics Tell Us About Saliency Models? , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Nils Eckardt,et al.  Healthy aging does not impair lower extremity motor flexibility while walking across an uneven surface. , 2018, Human movement science.

[8]  Charles Malleson,et al.  Fusing Visual and Inertial Sensors with Semantics for 3D Human Pose Estimation , 2018, International Journal of Computer Vision.

[9]  Jianfei Cai,et al.  Weakly-Supervised 3D Hand Pose Estimation from Monocular RGB Images , 2018, ECCV.

[10]  Jaap H. van Dieën,et al.  Where to Step? Contributions of Stance Leg Muscle Spindle Afference to Planning of Mediolateral Foot Placement for Balance Control in Young and Old Adults , 2018, Front. Physiol..

[11]  Iasonas Kokkinos,et al.  DensePose: Dense Human Pose Estimation in the Wild , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[12]  Natalie Vanicek,et al.  Spatiotemporal and plantar pressure patterns of 1000 healthy individuals aged 3-101 years. , 2017, Gait & posture.

[13]  Song-Chun Zhu,et al.  Monocular 3D Human Pose Estimation by Predicting Depth on Joints , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[14]  James J. Little,et al.  A Simple Yet Effective Baseline for 3d Human Pose Estimation , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[15]  Yichen Wei,et al.  Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[16]  Yichen Wei,et al.  Compositional Human Pose Regression , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[17]  Aaron C. Courville,et al.  Improved Training of Wasserstein GANs , 2017, NIPS.

[18]  Deva Ramanan,et al.  3D Human Pose Estimation = 2D Pose Estimation + Matching , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Francesc Moreno-Noguer,et al.  3D Human Pose Estimation from a Single Image via Distance Matrix Regression , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[20]  Yaser Sheikh,et al.  OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Xiaowei Zhou,et al.  Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Pose , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[22]  Juergen Gall,et al.  PoseTrack: Joint Multi-person Pose Estimation and Tracking , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[23]  François Chollet,et al.  Xception: Deep Learning with Depthwise Separable Convolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[24]  Kilian Q. Weinberger,et al.  Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[25]  Xiaolei Lv,et al.  Data-driven inverse dynamics for human motion , 2016, ACM Trans. Graph..

[26]  Olga Sorkine-Hornung,et al.  Balancing 3D Models with Movable Masses , 2016, VMV.

[27]  Georgios Tzimiropoulos,et al.  Human Pose Estimation via Convolutional Part Heatmap Regression , 2016, ECCV.

[28]  Peter V. Gehler,et al.  Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image , 2016, ECCV.

[29]  Zhenhua Wang,et al.  Synthesizing Training Images for Boosting Human 3D Pose Estimation , 2016, 2016 Fourth International Conference on 3D Vision (3DV).

[30]  Jia Deng,et al.  Stacked Hourglass Networks for Human Pose Estimation , 2016, ECCV.

[31]  Xiaowei Zhou,et al.  Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[32]  Steve Marschner,et al.  Matching Real Fabrics with Micro-Appearance Models , 2015, ACM Trans. Graph..

[33]  Karl M Newell,et al.  Compensatory mechanisms of balance to the scaling of arm-swing frequency. , 2015, Journal of biomechanics.

[34]  Kang Zheng,et al.  Combining local appearance and holistic view: Dual-Source Deep Neural Networks for human pose estimation , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[35]  Sergey Ioffe,et al.  Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.

[36]  Jonathan Tompson,et al.  Efficient object localization using Convolutional Networks , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[37]  Brian Wyvill,et al.  Robust iso-surface tracking for interactive character skinning , 2014, ACM Trans. Graph..

[38]  Olga Sorkine-Hornung,et al.  Spin-it , 2014, ACM Trans. Graph..

[39]  Alan L. Yuille,et al.  Articulated Pose Estimation by a Graphical Model with Image Dependent Pairwise Relations , 2014, NIPS.

[40]  Cristian Sminchisescu,et al.  Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[41]  Bernt Schiele,et al.  2D Human Pose Estimation: New Benchmark and State of the Art Analysis , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[42]  Jonathan Tompson,et al.  Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation , 2014, NIPS.

[43]  Pietro Perona,et al.  Microsoft COCO: Common Objects in Context , 2014, ECCV.

[44]  Christian Szegedy,et al.  DeepPose: Human Pose Estimation via Deep Neural Networks , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[45]  Sylvain Lefebvre,et al.  Make it stand , 2013, ACM Trans. Graph..

[46]  Julian Fiérrez,et al.  Comparative Analysis and Fusion of Spatiotemporal Information for Footstep Recognition , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[47]  Ming C. Lin,et al.  Example-guided physically based modal sound synthesis , 2013, ACM Trans. Graph..

[48]  Andrew L. Maas.  Rectifier Nonlinearities Improve Neural Network Acoustic Models , 2013 .

[49]  Francesc Moreno-Noguer,et al.  Single image 3D human pose estimation from noisy observations , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[50]  Elizabeth Eckstrom,et al.  Tai chi and postural stability in patients with Parkinson's disease. , 2012, The New England journal of medicine.

[51]  Tingting Mu,et al.  Gait recognition: highly unique dynamic plantar pressure patterns among 104 individuals , 2012, Journal of The Royal Society Interface.

[52]  Cristian Sminchisescu,et al.  Latent structured models for human pose estimation , 2011, 2011 International Conference on Computer Vision.

[53]  Li-Shan Chou,et al.  Center of mass and base of support interaction during gait. , 2011, Gait & posture.

[54]  Zhiming Ji,et al.  Measurement of balance in computer posturography: Comparison of methods--A brief review. , 2011, Journal of bodywork and movement therapies.

[55]  Günther Greiner,et al.  Automatic Patient Pose Estimation Using Pressure Sensing Mattresses , 2011, Bildverarbeitung für die Medizin.

[56]  Bruce Kupelnick,et al.  Tai Chi on psychological well-being: systematic review and meta-analysis , 2010, BMC complementary and alternative medicine.

[57]  Graham Arnold,et al.  Foot pressure differences in men and women. , 2010, Foot and ankle surgery : official journal of the European Society of Foot and Ankle Surgeons.

[58]  David J. Fleet,et al.  Physics-Based Person Tracking Using the Anthropomorphic Walker , 2010, International Journal of Computer Vision.

[59]  Michael J. Black,et al.  HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion , 2010, International Journal of Computer Vision.

[60]  David J. Fleet,et al.  Estimating contact dynamics , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[61]  Peter Norvig,et al.  The Unreasonable Effectiveness of Data , 2009, IEEE Intelligent Systems.

[62]  J. Duysens,et al.  A new method to normalize plantar pressure measurements for foot size and foot progression angle. , 2009, Journal of biomechanics.

[63]  Odest Chadwicke Jenkins,et al.  Physical simulation for probabilistic motion tracking , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[64]  A. Hof.  The 'extrapolated center of mass' concept suggests a simple control of balance in walking. , 2008, Human movement science.

[65]  A. Hof.  The equations of motion for a standing human reveal three mechanisms for balance. , 2007, Journal of biomechanics.

[66]  Christopher M. Bishop,et al.  Pattern Recognition and Machine Learning (Information Science and Statistics) , 2006 .

[67]  Edward D. Lemaire,et al.  Plantar Pressure Parameters for Dynamic Gait Stability Analysis , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[68]  A L Hof,et al.  The condition for dynamic stability. , 2005, Journal of biomechanics.

[69]  Ankur Agarwal,et al.  3D human pose from silhouettes by relevance vector regression , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[70]  Yi-Chung Pai,et al.  Movement Termination and Stability in Standing , 2003, Exercise and sport sciences reviews.

[71]  Hongwei Hsiao,et al.  Accuracy and precision of two in-shoe pressure measurement systems , 2002, Ergonomics.

[72]  Cun-Hui Zhang,et al.  The multivariate L1-median and associated data depth. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[73]  David A. Winter,et al.  Human balance and posture control during standing and walking , 1995 .

[74]  D. Winter,et al.  Trajectory of the body COG and COP during initiation and termination of gait , 1993 .

[75]  P. Rousseeuw,et al.  Alternatives to the Median Absolute Deviation , 1993 .

[76]  D. Shepard.  A two-dimensional interpolation function for irregularly-spaced data , 1968, ACM National Conference.

[77]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.