21.4 Gesture and Pose Analysis

Chapter Contents (Back)
Surveillance.

21.4.1 Human Posture, or Human Pose, Human Body Pose

Chapter Contents (Back)
Human Pose. Human Posture. Body Pose. Posture. Pose. Multiple People: See also Multi-Person Human Pose Desicriptions. Segment parts: See also Human Body Segmentation, Posture, Pose Related. Body shape analysis: See also Human Body Shape. See also Human Pose Tracking, Posture Tracking, Posture from Video, Pose from Motion. See also Articulated Human Pose Desicriptions. See also Human Pose from Silhouettes. See also Human Posture, Upper Body Posture, Arms. See also Human Motion Capture, Joint Information, Special Activities. See also Human Action Recognition and Detection Using Human Pose. See also Human Detection, People Detection, Pedestrians, Using Body Parts, Body Shape.

Lee, H.J., Chen, Z.,
Determination of 3D Human Body Postures from a Single View,
CVGIP(30), No. 2, May 1985, pp. 148-168.
Elsevier DOI BibRef 8505

Barrón, C.[Carlos], Kakadiaris, I.A.[Ioannis A.],
On the Improvement of Anthropometry and Pose Estimation from a Single Uncalibrated Image,
MVA(14), No. 4, September 2003, pp. 229-236.
Springer DOI 0309
BibRef
Earlier:
The Improvement of Anthropomery and Pose Estimation from a Single Uncalibrated Image,
HUMO00(53-60).
IEEE Top Reference. 0010
See also Model-Based Estimation of 3D Human Motion. BibRef

Barrón, C.[Carlos], Kakadiaris, I.A.[Ioannis A.],
Estimating Anthropometry and Pose from a Single Uncalibrated Image,
CVIU(81), No. 3, March 2001, pp. 269-284.
DOI Link 0001
BibRef
Earlier:
Estimating Anthropometry and Pose from a Single Image,
CVPR00(I: 669-676).
IEEE DOI 0005
See also Model-Based Estimation of 3D Human Motion. BibRef

Bruckstein, A.M.[Alfred M.], Holt, R.J.[Robert J.], Jean, Y.D.[Yves D.], Netravali, A.N.[Arun N.],
On the use of shadows in stance recovery,
IJIST(11), No. 5, 2000, pp. 315-330.
WWW Link. 0110
BibRef

Dimitrijevic, M., Lepetit, V., Fua, P.,
Human body pose detection using Bayesian spatio-temporal templates,
CVIU(103), No. 2-3, November-December 2006, pp. 127-139.
Elsevier DOI 0611
Keywords: Body pose detection; Spatio-temporal templates; Template matching; Chamfer matching BibRef

Kohli, P.[Pushmeet], Rihan, J.[Jonathan], Bray, M.[Matthieu], Torr, P.H.S.[Philip H. S.],
Simultaneous Segmentation and Pose Estimation of Humans Using Dynamic Graph Cuts,
IJCV(79), No. 3, September 2008, pp. xx-yy.
Springer DOI 0806
BibRef
Earlier: A3, A1, A4, Only:
PoseCut: Simultaneous Segmentation and 3D Pose Estimation of Humans Using Dynamic Graph-Cuts,
ECCV06(II: 642-655).
Springer DOI 0608
BibRef

Rahman, M.M.[M. Masudur], Ishikawa, S.[Seiji],
Human Posture Recognition: Eigenspace Tuning By A Mean Eigenspace,
IJIG(5), No. 4, October 2005, pp. 825-837. 0510
BibRef

Scherff, P.C.[Phillip-Christoph], Baciu, G.[George], Hu, J.L.[Jin-Lian],
Intuitive Parameterized Input Interface For Proportional Reshaping Of Human Bodies,
IJIG(8), No. 2, April 2008, pp. 299-325. 0804
BibRef

Yan, J., Shen, S., Li, Y., Liu, Y.,
An Optimization Based Framework for Human Pose Estimation,
SPLetters(17), No. 8, August 2010, pp. 766-769.
IEEE DOI 1007
BibRef

Kuo, P.[Paul], Makris, D.[Dimitrios], Nebel, J.C.[Jean-Christophe],
Integration of bottom-up/top-down approaches for 2D pose estimation using probabilistic Gaussian modelling,
CVIU(115), No. 2, February 2011, pp. 242-255.
Elsevier DOI 1102
Human body pose estimation; Stochastic clustering; Gaussian mixture modelling; Pattern classification; Object recognition; Confidence measure; Ground truth BibRef

Lewandowski, M.[Michal], Makris, D.[Dimitrios], Nebel, J.C.[Jean-Christophe],
Automatic configuration of spectral dimensionality reduction methods for 3D human pose estimation,
VS09(1314-1321).
IEEE DOI 0910
BibRef

Kuo, P.[Paul], Makris, D.[Dimitrios], Megherbi, N.[Najla], Nebel, J.C.[Jean-Christophe],
Integration of Local Image Cues for Probabilistic 2D Pose Recovery,
ISVC08(II: 214-223).
Springer DOI 0812
Fit 2-D human body model. BibRef

Xie, F., Xu, G., Cheng, Y., Tian, Y.,
Human body and posture recognition system based on an improved thinning algorithm,
IET-IPR(5), No. 5, 2011, pp. 420-428.
DOI Link 1108
BibRef

Chen, S.S.[Shou-Shun], Akselrod, P.[Polina], Zhao, B.[Bo], Perez-Carrasco, J.A.[Jose Antonio], Linares-Barranco, B.[Bernabe], Culurciello, E.[Eugenio],
Efficient Feedforward Categorization of Objects and Human Postures with Address-Event Image Sensors,
PAMI(34), No. 2, February 2012, pp. 302-314.
IEEE DOI 1112
Line feature models. See also NeuFlow: A runtime reconfigurable dataflow processor for vision. BibRef

Pourdamghani, N.[Nima], Rabiee, H.R.[Hamid R.], Faghri, F.[Fartash], Rohban, M.H.[Mohammad Hossein],
Graph based semi-supervised human pose estimation: When the output space comes to help,
PRL(33), No. 12, 1 September 2012, pp. 1529-1535.
Elsevier DOI 1208
Human pose estimation; Graph based; Semi-supervised; Manifold regularization BibRef

Pourdamghani, N.[Nima], Rabiee, H.R.[Hamid R.], Zolfaghari, M.[Mohammadreza],
Metric learning for graph based semi-supervised human pose estimation,
ICPR12(3386-3389).
WWW Link. 1302
BibRef

Tian, Y.[Yan], Sigal, L.[Leonid], de la Torre, F.[Fernando], Jia, Y.H.[Yong-Hua],
Canonical locality preserving Latent Variable Model for discriminative pose inference,
IVC(31), No. 3, March 2013, pp. 223-230.
Elsevier DOI 1303
Human pose estimation; Gaussian Mixture Regression; Latent Variable Model; Discriminative Model BibRef

Tian, Y.[Yan], Jia, Y.H.[Yong-Hua], Shi, Y.[Yuan], Liu, Y.[Yong], Ji, H.[Hao], Sigal, L.[Leonid],
Inferring 3D body pose using variational semi-parametric regression,
ICIP11(29-32).
IEEE DOI 1201
BibRef

Fergie, M.[Martin], Galata, A.[Aphrodite],
Mixtures of Gaussian process models for human pose estimation,
IVC(31), No. 12, 2013, pp. 949-957.
Elsevier DOI 1312
BibRef
Earlier:
Dynamical Pose Filtering for Mixtures of Gaussian Processes,
BMVC12(7).
DOI Link 1301
BibRef
Earlier:
Local Gaussian Processes for Pose Recognition from Noisy Inputs,
BMVC10(xx-yy).
HTML Version. 1009
Computer vision BibRef

Yamada, M.[Makoto], Sigal, L.[Leonid], Raptis, M.[Michalis],
Covariate Shift Adaptation for Discriminative 3D Pose Estimation,
PAMI(36), No. 2, February 2014, pp. 235-247.
IEEE DOI 1402
BibRef
Earlier:
No Bias Left behind: Covariate Shift Adaptation for Discriminative 3D Pose Estimation,
ECCV12(IV: 674-687).
Springer DOI 1210
Gaussian processes BibRef

Babagholami-Mohamadabadi, B., Jourabloo, A., Zarghami, A., Kasaei, S.,
A Bayesian Framework for Sparse Representation-Based 3-D Human Pose Estimation,
SPLetters(21), No. 3, March 2014, pp. 297-300.
IEEE DOI 1403
Bayes methods BibRef

Ionescu, C.[Catalin], Papava, D., Olaru, V., Sminchisescu, C.[Cristian],
Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments,
PAMI(36), No. 7, July 2014, pp. 1325-1339.
IEEE DOI 1407
Cameras BibRef

Ionescu, C.[Catalin], Li, F.X.[Fu-Xin], Sminchisescu, C.[Cristian],
Latent structured models for human pose estimation,
ICCV11(2220-2227).
IEEE DOI 1201
See also Structural SVM for visual localization and continuous state estimation. BibRef

Cho, E.[Eunji], Kim, D.J.[Dai-Jin],
Accurate Human Pose Estimation by Aggregating Multiple Pose Hypotheses Using Modified Kernel Density Approximation,
SPLetters(22), No. 4, April 2015, pp. 445-449.
IEEE DOI 1411
pose estimation BibRef

Li, S.J.[Si-Jin], Liu, Z.Q.[Zhi-Qiang], Chan, A.B.[Antoni B.],
Heterogeneous Multi-Task Learning for Human Pose Estimation with Deep Convolutional Neural Network,
IJCV(113), No. 1, May 2015, pp. 19-36.
Springer DOI 1506
BibRef
Earlier: DeepLearn14(488-495)
IEEE DOI 1409
BibRef
And: A1, A3, Only:
3D Human Pose Estimation from Monocular Images with Deep Convolutional Neural Network,
ACCV14(II: 332-347).
Springer DOI 1504
deep learning; human pose estimation; multi-task learning BibRef

Pons-Moll, G.[Gerard], Taylor, J.[Jonathan], Shotton, J.D.J.[Jamie D.J.], Hertzmann, A.[Aaron], Fitzgibbon, A.[Andrew],
Metric Regression Forests for Correspondence Estimation,
IJCV(113), No. 3, July 2015, pp. 163-175.
Springer DOI 1506
BibRef
Earlier:
Metric Regression Forests for Human Pose Estimation,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Taylor, J.[Jonathan], Shotton, J.D.J.[Jamie D.J.], Sharp, T.[Toby], Fitzgibbon, A.[Andrew],
The Vitruvian manifold: Inferring dense correspondences for one-shot human pose estimation,
CVPR12(103-110).
IEEE DOI 1208
BibRef

Hong, C.Q.[Chao-Qun], Yu, J.[Jun], Wan, J.[Jian], Tao, D.C.[Da-Cheng], Wang, M.[Meng],
Multimodal Deep Autoencoder for Human Pose Recovery,
IP(24), No. 12, December 2015, pp. 5659-5670.
IEEE DOI 1512
backpropagation BibRef

Dong, J.[Jian], Chen, Q.A.[Qi-Ang], Huang, Z., Yang, J.C.[Jian-Chao], Yan, S.C.[Shui-Cheng],
Parsing Based on Parselets: A Unified Deformable Mixture Model for Human Parsing,
PAMI(38), No. 1, January 2016, pp. 88-101.
IEEE DOI 1601
Deformable models BibRef

Dong, J.[Jian], Chen, Q.A.[Qi-Ang], Shen, X.H.[Xiao-Hui], Yang, J.C.[Jian-Chao], Yan, S.C.[Shui-Cheng],
Towards Unified Human Parsing and Pose Estimation,
CVPR14(843-850)
IEEE DOI 1409
Human Parsing; Human Pose Estimation BibRef

Tashiro, K.[Kazuhiro], Kawamura, T.[Takahiro], Sei, Y.[Yuichi], Nakagawa, H.[Hiroyuki], Tahara, Y.[Yasuyuki], Ohsuga, A.[Akihiko],
Iterative Improvement of Human Pose Classification Using Guide Ontology,
IEICE(E99-D), No. 1, January 2016, pp. 236-247.
WWW Link. 1601
BibRef

Hernández-Vela, A.[Antonio], Sclaroff, S.[Stan], Escalera, S.[Sergio],
Poselet-Based Contextual Rescoring for Human Pose Estimation via Pictorial Structures,
IJCV(118), No. 1, June 2016, pp. 49-64.
Springer DOI 1605
BibRef
Earlier: A1, A3, A2:
Contextual Rescoring for Human Pose Estimation,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Kang, X.[Xin], Yau, W.P.[Wai-Pan], Taylor, R.H.[Russell H.],
Simultaneous pose estimation and patient-specific model reconstruction from single image using maximum penalized likelihood estimation (MPLE),
PR(57), No. 1, 2016, pp. 61-69.
Elsevier DOI 1605
Pose estimation BibRef

Unzueta, L., Aranjuelo, N., Goenetxea, J., Rodriguez, M., Linaza, M.T.,
Contextualised learning-free three-dimensional body pose estimation from two-dimensional body features in monocular images,
IET-CV(10), No. 4, 2016, pp. 299-306.
DOI Link 1608
cameras BibRef

Liu, H.L.[Hong-Lin], Kong, D.H.[De-Hui], Wang, S.F.[Shao-Fan], Yin, B.C.[Bao-Cai],
Sparse Pose Regression via Componentwise Clustering Feature Point Representation,
MultMed(18), No. 7, July 2016, pp. 1233-1244.
IEEE DOI 1608
feature extraction. 2D pose of human body from range image. BibRef

Pishchulin, L.[Leonid], Wuhrer, S.[Stefanie], Helten, T.[Thomas], Theobalt, C.[Christian], Schiele, B.[Bernt],
Building statistical shape spaces for 3D human modeling,
PR(67), No. 1, 2017, pp. 276-286.
Elsevier DOI 1704
Statistical human body model BibRef

Sarafianos, N.[Nikolaos], Boteanu, B.[Bogdan], Ionescu, B.[Bogdan], Kakadiaris, I.A.[Ioannis A.],
3D Human pose estimation: A review of the literature and analysis of covariates,
CVIU(152), No. 1, 2016, pp. 1-20.
Elsevier DOI 1609
Survey, Human Pose. 3D Human pose estimation BibRef

Wu, Y., Lu, T., Yuan, Z., Wang, H.,
FreeScup: A Novel Platform for Assisting Sculpture Pose Design,
MultMed(19), No. 1, January 2017, pp. 183-195.
IEEE DOI 1612
Image reconstruction BibRef

Cho, J.C.[Jung-Chan], Lee, M.[Minsik], Oh, S.H.[Song-Hwai],
Single image 3D human pose estimation using a procrustean normal distribution mixture model and model transformation,
CVIU(155), No. 1, 2017, pp. 150-161.
Elsevier DOI 1702
Human pose estimation BibRef

Hara, K.[Kota], Chellappa, R.[Rama],
Growing Regression Tree Forests by Classification for Continuous Object Pose Estimation,
IJCV(122), No. 2, April 2017, pp. 292-312.
Springer DOI 1704
BibRef
Earlier:
Growing Regression Forests by Classification: Applications to Object Pose Estimation,
ECCV14(II: 552-567).
Springer DOI 1408
BibRef
Earlier:
Computationally Efficient Regression on a Dependency Graph for Human Pose Estimation,
CVPR13(3390-3397)
IEEE DOI 1309
Human Pose Estimation; Regression BibRef

Jammalamadaka, N.[Nataraj], Zisserman, A.[Andrew], Jawahar, C.V.,
Human pose search using deep networks,
IVC(59), No. 1, 2017, pp. 31-43.
Elsevier DOI 1704
BibRef
Earlier:
Human pose search using deep poselets,
FG15(1-8)
IEEE DOI 1508
Pose retrieval. image representation BibRef

Atrevi, D.F.[Dieudonné Fabrice], Vivet, D.[Damien], Duculty, F.[Florent], Emile, B.[Bruno],
A very simple framework for 3D human poses estimation using a single 2D image: Comparison of geometric moments descriptors,
PR(71), No. 1, 2017, pp. 389-401.
Elsevier DOI 1707
3D, Pose, estimation BibRef

Safi, K.[Khaled], Mohammed, S.[Samer], Albertsen, I.M.[Inke Marie], Delechelle, E.[Eric], Amirat, Y.[Yacine], Khalil, M.[Mohamad], Gracies, J.M.[Jean-Michel], Hutin, E.[Emilie],
Automatic analysis of human posture equilibrium using empirical mode decomposition,
SIViP(11), No. 6, September 2017, pp. 1081-1088.
Springer DOI 1708
BibRef

Gouiaa, R.[Rafik], Meunier, J.[Jean],
Learning cast shadow appearance for human posture recognition,
PRL(97), No. 1, 2017, pp. 54-60.
Elsevier DOI 1709
Cast shadows BibRef

Zhang, S., McCullagh, P., Zheng, H., Nugent, C.,
Situation Awareness Inferred From Posture Transition and Location: Derived From Smartphone and Smart home Sensors,
HMS(47), No. 6, December 2017, pp. 814-821.
IEEE DOI 1712
Accelerometers, Assisted living, Body sensor networks, Context awareness, Radiofrequency identification, Smart homes, wearable computers BibRef

Azrour, S.[Samir], Piérard, S.[Sébastien], Geurts, P.[Pierre], Van Droogenbroeck, M.[Marc],
A Two-Step Methodology for Human Pose Estimation Increasing the Accuracy and Reducing the Amount of Learning Samples Dramatically,
ACIVS17(3-14).
Springer DOI 1712
BibRef

Ning, G., Zhang, Z., He, Z.,
Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation,
MultMed(20), No. 5, May 2018, pp. 1246-1259.
IEEE DOI 1805
Biological system modeling, Fractals, Knowledge engineering, Neural networks, Pose estimation, Training, Human pose estimation, knowledge-guided learning BibRef

Petrov, I.[Ilia], Shakhuro, V.[Vlad], Konushin, A.[Anton],
Deep probabilistic human pose estimation,
IET-CV(12), No. 5, August 2018, pp. 578-585.
DOI Link 1807
BibRef

Rogez, G.[Grégory], Schmid, C.[Cordelia],
Image-Based Synthesis for Deep 3D Human Pose Estimation,
IJCV(126), No. 9, September 2018, pp. 993-1008.
Springer DOI 1809
BibRef

Rogez, G.[Grégory], Weinzaepfel, P., Schmid, C.[Cordelia],
LCR-Net++: Multi-Person 2D and 3D Pose Detection in Natural Images,
PAMI(42), No. 5, May 2020, pp. 1146-1161.
IEEE DOI 2004
BibRef
Earlier:
LCR-Net: Localization-Classification-Regression for Human Pose,
CVPR17(1216-1224)
IEEE DOI 1711
Pose estimation, Proposals, Joints, Heating systems, Training data, CNN. Computer architecture, Standards, Training. BibRef

Lim, J.[Jongin], Yoo, Y.J.[Young-Joon], Heo, B.[Byeongho], Choi, J.Y.[Jin Young],
Pose transforming network: Learning to disentangle human posture in variational auto-encoded latent space,
PRL(112), 2018, pp. 91-97.
Elsevier DOI 1809
Human pose transform, Disentangle hidden factors in latent space, Generative model, Variational auto-encoder BibRef

Dong, L., Chen, X., Wang, R., Zhang, Q., Izquierdo, E.[Ebroul],
ADORE: An Adaptive Holons Representation Framework for Human Pose Estimation,
CirSysVideo(28), No. 10, October 2018, pp. 2803-2813.
IEEE DOI 1811
Pose estimation, Detectors, Adaptation models, Training, Computational modeling, Image color analysis, Pose estimation, adaptivity BibRef

Nie, X., Feng, J., Xing, J., Xiao, S., Yan, S.,
Hierarchical Contextual Refinement Networks for Human Pose Estimation,
IP(28), No. 2, February 2019, pp. 924-936.
IEEE DOI 1811
Pose estimation, Complexity theory, Heating systems, Biological system modeling, Predictive models, Iterative methods, hierarchical contextual refinement network BibRef

Iqbal, U.[Umar], Doering, A.[Andreas], Yasin, H.[Hashim], Krüger, B.[Björn], Weber, A.[Andreas], Gall, J.[Juergen],
A dual-source approach for 3D human pose estimation from single images,
CVIU(172), 2018, pp. 37-49.
Elsevier DOI 1812
BibRef
Earlier: A2, A1, A4, A5, A6, Only:
A Dual-Source Approach for 3D Pose Estimation from a Single Image,
CVPR16(4948-4956)
IEEE DOI 1612
3D human pose estimation, Motion capture, 3D reconstruction, Articulated pose estimation BibRef

Liang, S.[Shuang], Sun, X.[Xiao], Wei, Y.C.[Yi-Chen],
Compositional Human Pose Regression,
CVIU(176-177), 2018, pp. 1-8.
Elsevier DOI 1812
BibRef

Sun, X.[Xiao], Xiao, B.[Bin], Wei, F.Y.[Fang-Yin], Liang, S.[Shuang], Wei, Y.C.[Yi-Chen],
Integral Human Pose Regression,
ECCV18(VI: 536-553).
Springer DOI 1810
BibRef

Wang, S., Xin, Y., Kong, D., Yin, B.,
Unsupervised Learning of Human Pose Distance Metric via Sparsity Locality Preserving Projections,
MultMed(21), No. 2, February 2019, pp. 314-327.
IEEE DOI 1902
Measurement, Robots, Resource management, Image recognition, Databases, Learning systems, Skeleton, Pose similarity, locality preserving projection BibRef

Yang, J.J.[Jing-Jing], Wan, L.[Lili], Xu, W.[Wanru], Wang, S.H.[Sheng-Hui],
3D human pose estimation from a single image via exemplar augmentation,
JVCIR(59), 2019, pp. 371-379.
Elsevier DOI 1903
Human pose estimation, Human pose recovery, Exemplar-based, Pose retrieval, Pose synthesis, Monocular BibRef

Gilbert, A.[Andrew], Trumble, M.[Matthew], Hilton, A.[Adrian], Collomosse, J.[John],
Fusing Visual and Inertial Sensors with Semantics for 3D Human Pose Estimation,
IJCV(127), No. 4, April 2019, pp. 381-397.
Springer DOI 1903
BibRef

Cha, G.[Geonho], Lee, M.[Minsik], Cho, J.C.[Jung-Chan], Oh, S.H.[Song-Hwai],
Deep pose consensus networks,
CVIU(182), 2019, pp. 64-70.
Elsevier DOI 1905
3D human pose estimation, Single-image-based 3D human pose estimation, Multiple-partial-hypothesis-based scheme. BibRef

Zhang, X.Y.[Xiao-Yan], Tang, Z.H.[Zhen-Hua], Hou, J.[Junhui], Hao, Y.B.[Yan-Bin],
3D human pose estimation via human structure-aware fully connected network,
PRL(125), 2019, pp. 404-410.
Elsevier DOI 1909
3D human pose estimation, Human structure, Fully connected network BibRef

Liu, J.[Jian], Rahmani, H.[Hossein], Akhtar, N.[Naveed], Mian, A.S.[Ajmal S.],
Learning Human Pose Models from Synthesized Data for Robust RGB-D Action Recognition,
IJCV(127), No. 10, October 2019, pp. 1545-1564.
Springer DOI 1909
BibRef

Spurlock, S., Souvenir, R.,
Multimodal 3D Human Pose Estimation from a Single Image,
3DV19(663-670)
IEEE DOI 1806
Training, Mutual information, Pose estimation, Solid modeling, CNN BibRef

Wu, Z.H.[Zhong-Hua], Lin, G.S.[Guo-Sheng], Cai, J.F.[Jian-Fei],
Keypoint based weakly supervised human parsing,
IVC(91), 2019, pp. 103801.
Elsevier DOI 1912
Human parsing, Weakly supervise, Iterative refinement, Keypoint, Skeleton, Correlation network BibRef

Chen, Y.C.[Yu-Cheng], Tian, Y.[Yingli], He, M.Y.[Ming-Yi],
Monocular human pose estimation: A survey of deep learning-based methods,
CVIU(192), 2020, pp. 102897.
Elsevier DOI 2002
Deep learning, Human pose estimation, Survey BibRef

Zheng, X.T.[Xiang-Tao], Chen, X.M.[Xiu-Mei], Lu, X.Q.[Xiao-Qiang],
A Joint Relationship Aware Neural Network for Single-Image 3D Human Pose Estimation,
IP(29), 2020, pp. 4747-4758.
IEEE DOI 2003
Pose estimation, Feature extraction, dual attention module BibRef

Wang, K.[Keze], Lin, L.[Liang], Jiang, C.H.[Chen-Han], Qian, C.[Chen], Wei, P.X.[Peng-Xu],
3D Human Pose Machines with Self-Supervised Learning,
PAMI(42), No. 5, May 2020, pp. 1069-1082.
IEEE DOI 2004
Pose estimation, Solid modeling, Task analysis, Deep learning, geometric deep learning BibRef

de Bem, R.[Rodrigo], Ghosh, A.[Arnab], Ajanthan, T.[Thalaiyasingam], Miksik, O.[Ondrej], Boukhayma, A.[Adnane], Siddharth, N., Torr, P.H.S.[Philip H.S.],
DGPose: Deep Generative Models for Human Body Analysis,
IJCV(128), No. 5, May 2020, pp. 1537-1563.
Springer DOI 2005
BibRef
Earlier: A1, A2, A3, A4, A6, A7, Only:
A Semi-supervised Deep Generative Model for Human Body Analysis,
HBU18(II:500-517).
Springer DOI 1905
BibRef

Miki, D.[Daisuke], Abe, S.[Shinya], Chen, S.[Shi], Demachi, K.[Kazuyuki],
Robust human pose estimation from distorted wide-angle images through iterative search of transformation parameters,
SIViP(14), No. 4, June 2020, pp. 693-700.
WWW Link. 2005
BibRef

Zhao, C.C.[Chen-Chen], Qian, Y.Q.[Ye-Qiang], Yang, M.[Ming],
Monocular pedestrian orientation estimation based on deep 2D-3D feedforward,
PR(100), 2020, pp. 107182.
Elsevier DOI 2005
Information feedforward, Logic relationship, Monocular vision, Orientation estimation BibRef

Bin, Y.R.[Yan-Rui], Chen, Z.M.[Zhao-Min], Wei, X.S.[Xiu-Shen], Chen, X.[Xinya], Gao, C.X.[Chang-Xin], Sang, N.[Nong],
Structure-aware human pose estimation with graph convolutional networks,
PR(106), 2020, pp. 107410.
Elsevier DOI 2006
Human pose estimation, Graph convolutional networks, Key points structural relations BibRef

Chen, Y.[Yu], Shen, C.H.[Chun-Hua], Wei, X.S.[Xiu-Shen], Liu, L.Q.[Ling-Qiao], Yang, J.[Jian],
Adversarial PoseNet: A Structure-Aware Convolutional Network for Human Pose Estimation,
ICCV17(1221-1230)
IEEE DOI 1802
feedforward neural nets, learning (artificial intelligence), pose estimation, Adversarial PoseNet, Training BibRef

Park, S.[Soonchan], Lee, S.B.[Sang-Baek], Park, J.[Jinah],
Data augmentation method for improving the accuracy of human pose estimation with cropped images,
PRL(136), 2020, pp. 244-250.
Elsevier DOI 2008
Data augmentation, Human pose estimation, Keypoint detection BibRef

Karanam, S.[Srikrishna], Li, R.[Ren], Yang, F.[Fan], Hu, W.[Wei], Chen, T.[Terrence], Wu, Z.Y.[Zi-Yan],
Towards Contactless Patient Positioning,
MedImg(39), No. 8, August 2020, pp. 2701-2710.
IEEE DOI 2008
Body pose, to enable automatic positioning. Cameras, Hospitals, Calibration, Computed tomography, Biomedical imaging, Telemedicine, Covid-19, shape BibRef

Ludl, D., Gulde, T., Curio, C.,
Enhancing Data-Driven Algorithms for Human Pose Estimation and Action Recognition Through Simulation,
ITS(21), No. 9, September 2020, pp. 3990-3999.
IEEE DOI 2008
Data models, Solid modeling, Databases, Computational modeling, Pose estimation, Training data, Simulation, autonomous vehicles BibRef

Sridhar Raj, S., Prasad, M.V.N.K.[Munaga V.N.K.], Balakrishnan, R.[Ramadoss],
Deep manifold clustering based optimal pseudo pose representation (DMC-OPPR) for unsupervised person re-identification,
IVC(101), 2020, pp. 103956.
Elsevier DOI 2009
Person re-identification, Clustering, Pose estimation, Representation, Computer vision, Deep learning BibRef


Cheng, B., Xiao, B., Wang, J., Shi, H., Huang, T.S., Zhang, L.,
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation,
CVPR20(5385-5394)
IEEE DOI 2008
Heating systems, Pose estimation, Convolution, Spatial resolution, Deconvolution, Training BibRef

Dorkenwald, M., Büchler, U., Ommer, B.,
Unsupervised Magnification of Posture Deviations Across Subjects,
CVPR20(8253-8263)
IEEE DOI 2008
Image reconstruction, Encoding, Training, Image coding, Image color analysis, Decoding, Computer vision BibRef

Huang, J., Zhu, Z., Guo, F., Huang, G.,
The Devil Is in the Details: Delving Into Unbiased Data Processing for Human Pose Estimation,
CVPR20(5699-5708)
IEEE DOI 2008
Pose estimation, Data processing, Standards, Heating systems, Training, Size measurement, Task analysis BibRef

Li, S., Ke, L., Pratama, K., Tai, Y., Tang, C., Cheng, K.,
Cascaded Deep Monocular 3D Human Pose Estimation With Evolutionary Training Data,
CVPR20(6172-6182)
IEEE DOI 2008
Training data, Bones, Pose estimation, Training BibRef

Isogawa, M., Yuan, Y., O'Toole, M., Kitani, K.M.,
Optical Non-Line-of-Sight Physics-Based 3D Human Pose Estimation,
CVPR20(7011-7020)
IEEE DOI 2008
Transient analysis, Nonlinear optics, Imaging, Pose estimation, Humanoid robots, Feature extraction BibRef

Zhang, F., Zhu, X., Dai, H., Ye, M., Zhu, C.,
Distribution-Aware Coordinate Representation for Human Pose Estimation,
CVPR20(7091-7100)
IEEE DOI 2008
Pose estimation, Standards, Decoding, Space heating, Image resolution, Encoding BibRef

Xie, R., Wang, C., Wang, Y.,
MetaFuse: A Pre-trained Fusion Model for Human Pose Estimation,
CVPR20(13683-13692)
IEEE DOI 2008
Cameras, Adaptation models, Pose estimation, Task analysis, Heating systems BibRef

Varamesh, A., Tuytelaars, T.,
Mixture Dense Regression for Object Detection and Human Pose Estimation,
CVPR20(13083-13092)
IEEE DOI 2008
Pose estimation, Object detection, Mixture models, Task analysis, Predictive models, Computer vision BibRef

Verma, M., Kumawat, S., Nakashima, Y., Raman, S.,
Yoga-82: A New Dataset for Fine-grained Classification of Human Poses,
VUHCS20(4472-4479)
IEEE DOI 2008
Dataset, Homan Pose. Legged locomotion, Wheels, Pose estimation, Computer vision, Visualization, Skeleton, Image resolution BibRef

Knoche, M., Sárándi, I., Leibe, B.,
Reposing Humans by Warping 3D Features,
VUHCS20(4499-4504)
IEEE DOI 2008
Decoding, Heating systems, Task analysis, Solid modeling, Measurement BibRef

Hwang, D., Kim, S., Monet, N., Koike, H., Bae, S.,
Lightweight 3D Human Pose Estimation Network Training Using Teacher-Student Learning,
WACV20(468-477)
IEEE DOI 2006
Pose estimation, Solid modeling, Heating systems, Training, Real-time systems BibRef

Kundu, J.N.[Jogendra Nath], Rahul, M.V., Patravali, J., Babu, R.V.[R. Venkatesh],
Unsupervised Cross-Dataset Adaptation via Probabilistic Amodal 3D Human Pose Completion,
WACV20(458-467)
IEEE DOI 2006
Pose estimation, Probabilistic logic, Cameras, Skeleton, Uncertainty BibRef

Ryou, S.[Serim], Jeong, S.G.[Seong-Gyun], Perona, P.[Pietro],
Anchor Loss: Modulating Loss Scale Based on Prediction Difficulty,
ICCV19(5991-6000)
IEEE DOI 2004
entropy, image classification, Modulation, learning (artificial intelligence), neural nets, pose estimation. BibRef

Tang, S., Tan, F., Cheng, K., Li, Z., Zhu, S., Tan, P.,
A Neural Network for Detailed Human Depth Estimation From a Single Image,
ICCV19(7749-7758)
IEEE DOI 2004
cameras, feature extraction, image colour analysis, learning (artificial intelligence), Skeleton BibRef

Cai, Y.J.[Yu-Jun], Ge, L.H.[Liu-Hao], Liu, J.[Jun], Cai, J.F.[Jian-Fei], Cham, T.J.[Tat-Jen], Yuan, J.S.[Jun-Song], Thalmann, N.M.[Nadia Magnenat],
Exploiting Spatial-Temporal Relationships for 3D Pose Estimation via Graph Convolutional Networks,
ICCV19(2272-2281)
IEEE DOI 2004
convolutional neural nets, feature extraction, graph theory, image representation, image sequences, Kernel BibRef

Wang, B., Adeli, E., Chiu, H., Huang, D., Niebles, J.C.,
Imitation Learning for Human Pose Prediction,
ICCV19(7123-7132)
IEEE DOI 2004
image motion analysis, neural net architecture, pose estimation, recurrent neural nets, supervised learning, BibRef

Duan, H., Lin, K., Jin, S., Liu, W., Qian, C., Ouyang, W.,
TRB: A Novel Triplet Representation for Understanding 2D Human Body,
ICCV19(9478-9487)
IEEE DOI 2004
image capture, image representation, learning (artificial intelligence), message passing, Convolution BibRef

Venkat, A., Patel, C., Agrawal, Y., Sharma, A.,
HumanMeshNet: Polygonal Mesh Recovery of Humans,
3D-Wild19(2178-2187)
IEEE DOI 2004
computational geometry, computer vision, image reconstruction, image representation, image resolution, SMPL BibRef

Hassan, M., Choutas, V., Tzionas, D., Black, M.,
Resolving 3D Human Pose Ambiguities With 3D Scene Constraints,
ICCV19(2282-2292)
IEEE DOI 2004
Code, Human Pose.
WWW Link. image motion analysis, image reconstruction, image sequences, pose estimation, 3D human pose ambiguities, scene constraints, BibRef

Sharma, S., Varigonda, P.T., Bindal, P., Sharma, A., Jain, A.,
Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking,
ICCV19(2325-2334)
IEEE DOI 2004
Code, Human Pose.
WWW Link. learning (artificial intelligence), neural nets, pose estimation, solid modelling, stereo image processing, Heating systems BibRef

Martinez, G.H., Raaj, Y., Idrees, H., Xiang, D., Joo, H., Simon, T., Sheikh, Y.,
Single-Network Whole-Body Pose Estimation,
ICCV19(6981-6990)
IEEE DOI 2004
Code, Human Pose.
WWW Link. computational complexity, face recognition, image resolution, learning (artificial intelligence), pose estimation, Three-dimensional displays BibRef

Iskakov, K., Burkov, E., Lempitsky, V., Malkov, Y.,
Learnable Triangulation of Human Pose,
ICCV19(7717-7726)
IEEE DOI 2004
Gaussian processes, object tracking, pose estimation, user interfaces, human pose, multiview 3D, triangulation methods, Detectors BibRef

Chen, C.H.[Ching-Hang], Tyagi, A.[Ambrish], Agrawal, A.[Amit], Drover, D.[Dylan], Rohith, M.V., Stojanov, S.[Stefan], Rehg, J.M.[James M.],
Unsupervised 3D Pose Estimation With Geometric Self-Supervision,
CVPR19(5707-5717).
IEEE DOI 2002
3D human pose from 2D skeletal joints. BibRef

Gong, K.[Ke], Gao, Y.M.[Yi-Ming], Liang, X.D.[Xiao-Dan], Shen, X.H.[Xiao-Hui], Wang, M.[Meng], Lin, L.[Liang],
Graphonomy: Universal Human Parsing via Graph Transfer Learning,
CVPR19(7442-7451).
IEEE DOI 2002
BibRef

Yang, L.[Lu], Song, Q.[Qing], Wang, Z.H.[Zhi-Hui], Jiang, M.[Ming],
Parsing R-CNN for Instance-Level Human Analysis,
CVPR19(364-373).
IEEE DOI 2002
BibRef

Sun, K.[Ke], Xiao, B.[Bin], Liu, D.[Dong], Wang, J.D.[Jing-Dong],
Deep High-Resolution Representation Learning for Human Pose Estimation,
CVPR19(5686-5696).
IEEE DOI 2002
BibRef

Li, C.[Chen], Lee, G.H.[Gim Hee],
Generating Multiple Hypotheses for 3D Human Pose Estimation With Mixture Density Network,
CVPR19(9879-9887).
IEEE DOI 2002
BibRef

Chen, X.P.[Xi-Peng], Lin, K.Y.[Kwan-Yee], Liu, W.T.[Wen-Tao], Qian, C.[Chen], Lin, L.[Liang],
Weakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose Estimation,
CVPR19(10887-10896).
IEEE DOI 2002
BibRef

Habibie, I.[Ikhsanul], Xu, W.[Weipeng], Mehta, D.[Dushyant], Pons-Moll, G.[Gerard], Theobalt, C.[Christian],
In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations,
CVPR19(10897-10906).
IEEE DOI 2002
BibRef

Kreiss, S.[Sven], Bertoni, L.[Lorenzo], Alahi, A.[Alexandre],
PifPaf: Composite Fields for Human Pose Estimation,
CVPR19(11969-11978).
IEEE DOI 2002
BibRef

Arnab, A.[Anurag], Doersch, C.[Carl], Zisserman, A.[Andrew],
Exploiting Temporal Context for 3D Human Pose Estimation in the Wild,
CVPR19(3390-3399).
IEEE DOI 2002
BibRef

Zhao, L.[Long], Peng, X.[Xi], Tian, Y.[Yu], Kapadia, M.[Mubbasir], Metaxas, D.N.[Dimitris N.],
Semantic Graph Convolutional Networks for 3D Human Pose Regression,
CVPR19(3420-3430).
IEEE DOI 2002
BibRef

Zhang, F.[Feng], Zhu, X.T.[Xia-Tian], Ye, M.[Mao],
Fast Human Pose Estimation,
CVPR19(3512-3521).
IEEE DOI 2002
BibRef

Li, Y.N.[Yi-Ning], Huang, C.[Chen], Loy, C.C.[Chen Change],
Dense Intrinsic Appearance Flow for Human Pose Transfer,
CVPR19(3688-3697).
IEEE DOI 2002
BibRef

Moon, G.[Gyeongsik], Chang, J.Y.[Ju Yong], Lee, K.M.[Kyoung Mu],
PoseFix: Model-Agnostic General Human Pose Refinement Network,
CVPR19(7765-7773).
IEEE DOI 2002
BibRef

Wandt, B.[Bastian], Rosenhahn, B.[Bodo],
RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation,
CVPR19(7774-7783).
IEEE DOI 2002
BibRef

Kocabas, M.[Muhammed], Karagoz, S.[Salih], Akbas, E.[Emre],
Self-Supervised Learning of 3D Human Pose Using Multi-View Geometry,
CVPR19(1077-1086).
IEEE DOI 2002
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Martin, J.B.[Jesus Bujalance], Moutarde, F.[Fabien],
Real-time Gestural Control of Robot Manipulator Through Deep Learning Human-pose Inference,
CVS19(565-572).
Springer DOI 1912
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Knyaz, V.A., Maksimov, A.A., Novikov, M.M.,
Vision Based Automated Anthropological Measurements and Analysis,
PTVSBB19(117-122).
DOI Link 1912
BibRef

Chu, S.W., Song, Y., Zouo, J.J., Cai, W.,
Human Pose Estimation Using Deep Convolutional Densenet Hourglass Network with Intermediate Points Voting,
ICIP19(594-598)
IEEE DOI 1910
Deep learning, convolution neural network, human pose estimation. BibRef

Benzine, A., Chabot, F., Luvison, B., Pham, Q.C., Achard, C.,
PandaNet: Anchor-Based Single-Shot Multi-Person 3D Pose Estimation,
CVPR20(6855-6864)
IEEE DOI 2008
BibRef
Earlier: A1, A3, A4, A5, Only:
Deep, Robust and Single Shot 3D Multi-Person Human Pose Estimation from Monocular Images,
ICIP19(584-588)
IEEE DOI 1910
Pose estimation, Heating systems, Image resolution, Solid modeling, Skeleton. multi-person, 3D human pose estimation. BibRef

Neumann, L.[Lukáš], Vedaldi, A.[Andrea],
Tiny People Pose,
ACCV18(III:558-574).
Springer DOI 1906
BibRef

Zhuang, W.L.[Wen-Lin], Peng, C.[Cong], Xia, S.[Siyu], Wang, Y.G.[Yan-Gang],
Multi-scale Adaptive Structure Network for Human Pose Estimation from Color Images,
ACCV18(I:643-658).
Springer DOI 1906
BibRef

Yoshiyasu, Y.[Yusuke], Sagawa, R.[Ryusuke], Ayusawa, K.[Ko], Murai, A.[Akihiko],
Skeleton Transformer Networks: 3D Human Pose and Skinned Mesh from Single RGB Image,
ACCV18(IV:485-500).
Springer DOI 1906
BibRef

Pelka, O.[Obioma], Nensa, F.[Felix], Friedrich, C.M.[Christoph M.],
Optimizing Body Region Classification with Deep Convolutional Activation Features,
WiCV-E18(IV:699-704).
Springer DOI 1905
BibRef

Sayed, M.R., Sim, T., Lim, J., Ma, K.T.,
Which Body Is Mine?,
WACV19(829-838)
IEEE DOI 1904
anthropometry, convolutional neural nets, correlation methods, image matching, pose estimation, Image recognition BibRef

Nibali, A., He, Z., Morgan, S., Prendergast, L.,
3D Human Pose Estimation With 2D Marginal Heatmaps,
WACV19(1477-1485)
IEEE DOI 1904
image colour analysis, inference mechanisms, neural nets, pose estimation, statistical analysis, stereo image processing, Solid modeling BibRef

Nie, X., Feng, J., Zuo, Y., Yan, S.,
Human Pose Estimation with Parsing Induced Learner,
CVPR18(2100-2108)
IEEE DOI 1812
Pose estimation, Adaptation models, Feature extraction, Predictive models, Semantics, Task analysis, Benchmark testing BibRef

Peng, X., Tang, Z., Yang, F., Feris, R.S., Metaxas, D.,
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation,
CVPR18(2226-2234)
IEEE DOI 1812
Training, Pose estimation, Generators, Neural networks, Task analysis, Data models BibRef

Saint, A., Ahmed, E., Shabayek, A.E.R., Cherenkova, K., Gusev, G., Aouada, D., Ottersten, B.,
3DBodyTex: Textured 3D Body Dataset,
3DV18(495-504)
IEEE DOI 1812
computer vision, image resolution, image texture, solid modelling, textured 3D body dataset, static 3D body scans, 3D body scans BibRef

Yang, W., Ouyang, W., Wang, X., Ren, J., Li, H., Wang, X.,
3D Human Pose Estimation in the Wild by Adversarial Learning,
CVPR18(5255-5264)
IEEE DOI 1812
Pose estimation, Generators, Heating systems, Joints, Task analysis BibRef

Güler, R.A., Neverova, N., Kokkinos, I.,
DensePose: Dense Human Pose Estimation in the Wild,
CVPR18(7297-7306)
IEEE DOI 1812
Pose estimation, Task analysis, Solid modeling, Training, Pipelines, Deformable models BibRef

Pavlakos, G., Zhou, X., Daniilidis, K.,
Ordinal Depth Supervision for 3D Human Pose Estimation,
CVPR18(7307-7316)
IEEE DOI 1812
Training, Image reconstruction, Pose estimation, Hip, Benchmark testing BibRef

Nie, X.C.[Xue-Cheng], Feng, J.[Jiashi], Yan, S.C.[Shui-Cheng],
Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation,
ECCV18(VI: 519-534).
Springer DOI 1810
BibRef

Tang, W.[Wei], Yu, P.[Pei], Wu, Y.[Ying],
Deeply Learned Compositional Models for Human Pose Estimation,
ECCV18(III: 197-214).
Springer DOI 1810
BibRef

Chen, Q., Zhang, C., Liu, W., Wang, D.,
SHPD: Surveillance Human Pose Dataset and Performance Evaluation for Coarse-Grained Pose Estimation,
ICIP18(4088-4092)
IEEE DOI 1809
Surveillance, Pose estimation, Cameras, Lighting, Benchmark testing, Task analysis, Performance evaluation, pose estimation, global-pose BibRef

Hu, H.M.[Hui-Min], Bai, Y.H.[Ya-Hui], Li, Y.X.[Yin-Xia], Wu, H.M.[Hai-Mei], Luo, L.[Ling], Wang, R.[Rui], Hong, P.[Pu],
Research on Ergonomics Design of the Height and Operation Force for Furniture Lockset,
DHM18(64-74).
Springer DOI 1807
BibRef

Friemert, D.[Daniel], Saala, F.[Florian], Hartmann, U.[Ulrich], Ellegast, R.[Rolf],
Similarities and Differences in Posture During Simulated Order Picking in Real Life and Virtual Reality,
DHM18(41-53).
Springer DOI 1807
BibRef

McLaughlin, N.[Niall], Martinez del Rincon, J.[Jesus],
Refining the Pose: Training and Use of Deep Recurrent Autoencoders for Improving Human Pose Estimation,
AMDO18(11-23).
Springer DOI 1807
BibRef

Rafi, U.[Umer], Leibe, B.[Bastian], Gall, J.[Juergen], Kostrikov, I.[Ilya],
An Efficient Convolutional Network for Human Pose Estimation,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Tekin, B., Sinha, S.N., Fua, P.,
Real-Time Seamless Single Shot 6D Object Pose Prediction,
CVPR18(292-301)
IEEE DOI 1812
Pose estimation, Solid modeling, Task analysis, Computer architecture BibRef

Tekin, B., Márquez-Neila, P., Salzmann, M., Fua, P.,
Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation,
ICCV17(3961-3970)
IEEE DOI 1802
image fusion, learning (artificial intelligence), motion estimation, pose estimation, 2D joint locations, BibRef

Ronchi, M.R.[Matteo Ruggero], Perona, P.[Pietro],
Benchmarking and Error Diagnosis in Multi-instance Pose Estimation,
ICCV17(369-378)
IEEE DOI 1802
computer vision, estimation theory, learning (artificial intelligence), pose estimation, Wrist BibRef

Wang, H., Liang, W., Yu, L.F.,
Transferring Objects: Joint Inference of Container and Human Pose,
ICCV17(2952-2960)
IEEE DOI 1802
computer vision, inference mechanisms, learning (artificial intelligence), pose estimation, BibRef

Liu, B., Ferrari, V.,
Active Learning for Human Pose Estimation,
ICCV17(4373-4382)
IEEE DOI 1802
learning (artificial intelligence), pose estimation, active learning framework, active learning process, Uncertainty BibRef

Sun, K., Lan, C., Xing, J., Zeng, W., Liu, D., Wang, J.,
Human Pose Estimation Using Global and Local Normalization,
ICCV17(5600-5608)
IEEE DOI 1802
convolution, learning (artificial intelligence), neural nets, pose estimation, articulated pose estimation, Wrist BibRef

Yang, W., Li, S., Ouyang, W.L.[Wan-Li], Li, H., Wang, X.G.[Xiao-Gang],
Learning Feature Pyramids for Human Pose Estimation,
ICCV17(1290-1299)
IEEE DOI 1802
computer vision, convolution, feature extraction, image classification, image representation, Visualization BibRef

Sciortino, G.[Giuseppa], Farinella, G.M.[Giovanni Maria], Battiato, S.[Sebastiano], Leo, M.[Marco], Distante, C.[Cosimo],
On the Estimation of Children's Poses,
CIAP17(II:410-421).
Springer DOI 1711
BibRef

Tome, D.[Denis], Russell, C.[Chris], Agapito, L.[Lourdes],
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image,
CVPR17(5689-5698)
IEEE DOI 1711
Single RGB image. Data models, Pose estimation, Predictive models, Probabilistic logic, Solid modeling BibRef

Popa, A.I., Zanfir, M., Sminchisescu, C.,
Deep Multitask Architecture for Integrated 2D and 3D Human Sensing,
CVPR17(4714-4723)
IEEE DOI 1711
Biological system modeling, Pose estimation, Semantics, Solid modeling, Training, Two, dimensional, displays BibRef

Tanabe, S.[Satoshi], Yamanaka, R.[Ryosuke], Tomono, M.[Mitsuru], Ito, M.[Makiko], Ishihara, T.[Teruo],
Real-Time Human Pose Estimation via Cascaded Neural Networks Embedded with Multi-task Learning,
CAIP17(II: 241-252).
Springer DOI 1708
BibRef

Marras, I.[Ioannis], Palasek, P.[Petar], Patras, I.[Ioannis],
Deep Mixture of MRFs for Human Pose Estimation,
ACCV18(III:717-733).
Springer DOI 1906
BibRef
And:
Deep Globally Constrained MRFs for Human Pose Estimation,
ICCV17(3486-3495)
IEEE DOI 1802
BibRef
Earlier:
Deep Refinement Convolutional Networks for Human Pose Estimation,
FG17(446-453)
IEEE DOI 1707
Markov processes, convolution, neural net architecture, pose estimation, random processes, ConvNet, Markov Random Field. Adaptation models, Data models, Heating systems, Image resolution, Pose estimation BibRef

Ismail, H., Radwan, I., Suominen, H., Waddington, G., Goecke, R.,
Human Postural Sway Estimation from Noisy Observations,
FG17(454-461)
IEEE DOI 1707
Cameras, Feature extraction, Foot, Force, Legged locomotion, Tracking BibRef

Belagiannis, V., Zisserman, A.,
Recurrent Human Pose Estimation,
FG17(468-475)
IEEE DOI 1707
Context, Context modeling, Convolution, Detectors, Heating systems, Predictive models, Training BibRef

Ai, B., Zhou, Y.[Yu], Yu, Y.[Yao], Du, S.[Sidan],
Human Pose Estimation Using Deep Structure Guided Learning,
WACV17(1224-1231)
IEEE DOI 1609
Biological system modeling, Computer vision, Feature extraction, Heating systems, Kernel, Neural networks, Pose, estimation See also Markerless Motion Capture of Human Body Using PSO with Single Depth Camera. BibRef

Farrajota, M., Rodrigues, J.M.F.[Joăo M.F.], du Buf, J.M.H.[J.M. Hans],
Human Pose Estimation by a Series of Residual Auto-Encoders,
IbPRIA17(131-139).
Springer DOI 1706
BibRef

Sarafianos, N., Nikou, C., Kakadiaris, I.A.,
Predicting privileged information for height estimation,
ICPR16(3115-3120)
IEEE DOI 1705
Biometrics (access control), Estimation, Length measurement, Prediction algorithms, Predictive models, Support vector machines, Training BibRef

Ni, S.C.[Shou-Cheng], Liu, W.W.[Wei-Wei], Cheng, H.[Hao], Zhang, C.Y.[Chong-Yang],
Visually Similar K-poselets Based Human Pose Recognition,
BEST16(III: 426-440).
Springer DOI 1704
BibRef

Brau, E., Jiang, H.,
3D Human Pose Estimation via Deep Learning from 2D Annotations,
3DV16(582-591)
IEEE DOI 1701
cameras BibRef

Chen, W., Wang, H., Li, Y., Su, H., Wang, Z., Tu, C., Lischinski, D., Cohen-Or, D., Chen, B.,
Synthesizing Training Images for Boosting Human 3D Pose Estimation,
3DV16(479-488)
IEEE DOI 1701
convolution BibRef

Ghezelghieh, M.F., Kasturi, R., Sarkar, S.,
Learning Camera Viewpoint Using CNN to Improve 3D Body Pose Estimation,
3DV16(685-693)
IEEE DOI 1701
cameras BibRef

Kwak, S.[Suha], Cho, M.S.[Min-Su], Laptev, I.[Ivan],
Thin-Slicing for Pose: Learning to Understand Pose without Explicit Pose Estimation,
CVPR16(4938-4947)
IEEE DOI 1612
BibRef

Zhou, X.Y.[Xing-Yi], Sun, X.[Xiao], Zhang, W.[Wei], Liang, S.[Shuang], Wei, Y.C.[Yi-Chen],
Deep Kinematic Pose Regression,
DeepLearn16(III: 186-201).
Springer DOI 1611
BibRef

Lifshitz, I.[Ita], Fetaya, E.[Ethan], Ullman, S.[Shimon],
Human Pose Estimation Using Deep Consensus Voting,
ECCV16(II: 246-260).
Springer DOI 1611
BibRef

Jung, H.Y.[Ho Yub], Suh, Y.M.[Yu-Min], Moon, G.[Gyeongsik], Lee, K.M.[Kyoung Mu],
A Sequential Approach to 3D Human Pose Estimation: Separation of Localization and Identification of Body Joints,
ECCV16(V: 747-761).
Springer DOI 1611
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Newell, A.[Alejandro], Yang, K.[Kaiyu], Deng, J.[Jia],
Stacked Hourglass Networks for Human Pose Estimation,
ECCV16(VIII: 483-499).
Springer DOI 1611
BibRef

Guo, C., Ruan, S., Liang, X.,
A strong bilayer appearance model for human pose estimation from a high freedom still image,
ICIP16(1284-1288)
IEEE DOI 1610
Benchmark testing BibRef

Liu, H.[Hong], Ma, L.[Liqian],
Online person orientation estimation based on classifier update,
ICIP15(1568-1572)
IEEE DOI 1512
Multi-class classification BibRef

Wang, L.[Lei], Zhao, X.[Xu], Liu, Y.C.[Yun-Cai],
Adaptive appearance learning for human pose estimation,
ICIP15(1125-1129)
IEEE DOI 1512
BibRef

Singh, S.[Saurabh], Hoiem, D.[Derek], Forsyth, D.A.[David A.],
Learning a sequential search for landmarks,
CVPR15(3422-3430)
IEEE DOI 1510
humans or birds. BibRef

Tompson, J.[Jonathan], Goroshin, R.[Ross], Jain, A.[Arjun], Le Cun, Y.L.[Yann L.], Bregler, C.[Christoph],
Efficient object localization using Convolutional Networks,
CVPR15(648-656)
IEEE DOI 1510
BibRef

Jung, H.Y.[Ho Yub], Lee, S.[Soochahn], Heo, Y.S.[Yong Seok], Yun, I.D.[Il Dong],
Random tree walk toward instantaneous 3D human pose estimation,
CVPR15(2467-2474)
IEEE DOI 1510
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Fan, X.C.[Xiao-Chuan], Zheng, K.[Kang], Lin, Y.W.[Yue-Wei], Wang, S.[Song],
Combining local appearance and holistic view: Dual-Source Deep Neural Networks for human pose estimation,
CVPR15(1347-1355)
IEEE DOI 1510
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Akhter, I.[Ijaz], Black, M.J.[Michael J.],
Pose-conditioned joint angle limits for 3D human pose reconstruction,
CVPR15(1446-1455)
IEEE DOI 1510
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Zakharov, A.A., Barinov, A.E., Zhiznyakov, A.L.,
Recognition of Human Pose from Images Based on Graph Spectra,
PTVSBB15(9-12).
DOI Link 1508
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Shen, W.[Wei], Lei, R.[Rui], Zeng, D.[Dan], Zhang, Z.J.[Zhi-Jiang],
Regularity Guaranteed Human Pose Correction,
ACCV14(II: 242-256).
Springer DOI 1504
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Tsatsoulis, P.D.[P. Daphne], Forsyth, D.A.[David A.],
Easy Minimax Estimation with Random Forests for Human Pose Estimation,
ChaLearn14(669-684).
Springer DOI 1504
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Heili, A.[Alexandre], Varadarajan, J.[Jagannadan], Ghanem, B.[Bernard], Ahuja, N.[Narendra], Odobez, J.M.[Jean-Marc],
Improving head and body pose estimation through semi-supervised manifold alignment,
ICIP14(1912-1916)
IEEE DOI 1502
Couplings BibRef

Khalid, A.R.[Abdul Rafay], Hassan, A.[Ali], Taj, M.[Murtaza],
Efficient 2D human pose estimation using mean-shift,
ICIP14(3387-3391)
IEEE DOI 1502
Estimation BibRef

Xia, D.X.[Dao-Xun], Su, S.Z.[Song-Zhi], Li, S.Z.[Shao-Zi], Jodoin, P.M.[Pierre-Marc],
Lying-pose detection with training dataset expansion,
ICIP14(3377-3381)
IEEE DOI 1502
Cameras BibRef

Zhang, Z.X.[Zhao-Xiang], Hao, J.L.[Jian-Liang], Wang, Y.H.[Yun-Hong], Zhao, Y.H.[Yu-Hang],
Enhanced Human Parsing with Multiple Feature Fusion and Augmented Pose Model,
ICPR14(369-374)
IEEE DOI 1412
Biological system modeling BibRef

Zerrouki, N., Houacine, A.,
Automatic Classification of Human Body Postures Based on Curvelet Transform,
ICIAR14(I: 329-337).
Springer DOI 1410
BibRef

Ionescu, C.[Catalin], Carreira, J.[Joao], Sminchisescu, C.[Cristian],
Iterated Second-Order Label Sensitive Pooling for 3D Human Pose Estimation,
CVPR14(1661-1668)
IEEE DOI 1409
BibRef

Wang, C.Y.[Chun-Yu], Wang, Y.Z.[Yi-Zhou], Lin, Z.C.[Zhou-Chen], Yuille, A.L.[Alan L.], Gao, W.[Wen],
Robust Estimation of 3D Human Poses from a Single Image,
CVPR14(2369-2376)
IEEE DOI 1409
3D human pose estimation BibRef

Ghiasi, G.[Golnaz], Yang, Y.[Yi], Ramanan, D.[Deva], Fowlkes, C.C.[Charless C.],
Parsing Occluded People,
CVPR14(2401-2408)
IEEE DOI 1409
Object Detection; Occlusion; Pose Estimation BibRef

Fan, X.C.[Xiao-Chuan], Zheng, K.[Kang], Zhou, Y.[Youjie], Wang, S.[Song],
Pose Locality Constrained Representation for 3D Human Pose Reconstruction,
ECCV14(I: 174-188).
Springer DOI 1408
BibRef

Dong, J.[Jian], Chen, Q.A.[Qi-Ang], Xia, W.[Wei], Huang, Z.Y.[Zhong-Yang], Yan, S.C.[Shui-Cheng],
A Deformable Mixture Parsing Model with Parselets,
ICCV13(3408-3415)
IEEE DOI 1403
BibRef

Andriluka, M.[Mykhaylo], Pishchulin, L.[Leonid], Gehler, P.[Peter], Schiele, B.[Bernt],
2D Human Pose Estimation: New Benchmark and State of the Art Analysis,
CVPR14(3686-3693)
IEEE DOI 1409
BibRef
Earlier: A2, A1, A3, A4:
Strong Appearance and Expressive Spatial Models for Human Pose Estimation,
ICCV13(3487-3494)
IEEE DOI 1403
human pose estimation; performance evaluation BibRef

Lehrmann, A.M.[Andreas M.], Gehler, P.V.[Peter V.], Nowozin, S.[Sebastian],
A Non-parametric Bayesian Network Prior of Human Pose,
ICCV13(1281-1288)
IEEE DOI 1403
Bayesian network BibRef

Radwan, I.[Ibrahim], Dhall, A.[Abhinav], Goecke, R.[Roland],
Monocular Image 3D Human Pose Estimation under Self-Occlusion,
ICCV13(1888-1895)
IEEE DOI 1403
3D pose reconstruction; pose estimation; self-occlusion BibRef

Burgos-Artizzu, X.[Xavier], Hall, D.[David], Perona, P.[Pietro], Dollar, P.[Piotr],
Merging Pose Estimates Across Space and Time,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Chen, Y.P.[Yin-Peng], Liu, Z.C.[Zi-Cheng], Zhang, Z.Y.[Zheng-You],
Tensor-Based Human Body Modeling,
CVPR13(105-112)
IEEE DOI 1309
Human Body Modeling; Tensor Decomposition BibRef

Wang, F.[Fang], Li, Y.[Yi],
Beyond Physical Connections: Tree Models in Human Pose Estimation,
CVPR13(596-603)
IEEE DOI 1309
graphical model; human pose estimation; object recognition BibRef

Joo, J.[Jungseock], Wang, S.[Shuo], Zhu, S.C.[Song-Chun],
Human Attribute Recognition by Rich Appearance Dictionary,
ICCV13(721-728)
IEEE DOI 1403
Fine-grained Recognition; Human Attribute; Weakly-Supervised Learning BibRef

Marcos-Ramiro, A., Pizarro-Perez, D., Marron-Romera, M., Nguyen, L., Gatica-Perez, D.[Daniel],
Body communicative cue extraction for conversational analysis,
FG13(1-8)
IEEE DOI 1309
feature extraction. Non-verbal communication. Gestures, etc. BibRef

Nodari, A.[Angelo], Vanetti, M.[Marco], Gallo, I.[Ignazio],
Visual Attribute Extraction Using Human Pose Estimation,
IbPRIA13(350-357).
Springer DOI 1307
BibRef

Duan, K.[Kun], Batra, D.[Dhruv], Crandall, D.[David],
A Multi-layer Composite Model for Human Pose Estimation,
BMVC12(116).
DOI Link 1301
BibRef

Jammalamadaka, N.[Nataraj], Zisserman, A.[Andrew], Eichner, M.[Marcin], Ferrari, V.[Vittorio], Jawahar, C.V.,
Has My Algorithm Succeeded? An Evaluator for Human Pose Estimators,
ECCV12(III: 114-128).
Springer DOI 1210
BibRef

Tian, Y.D.[Yuan-Dong], Zitnick, C.L.[C. Lawrence], Narasimhan, S.G.[Srinivasa G.],
Exploring the Spatial Hierarchy of Mixture Models for Human Pose Estimation,
ECCV12(V: 256-269).
Springer DOI 1210
See also Globally Optimal Estimation of Nonrigid Image Distortion. BibRef

Oh, C.M.[Chi-Min], Lee, Y.C.[Yong-Cheol], Bae, K.T.[Ki-Tae], Lee, C.W.[Chil-Woo],
Adaptive Exemplar-based Particle Filter for 2d Human Pose Estimation,
ISVC12(II: 609-615).
Springer DOI 1209
BibRef

Sun, M.[Min], Telaprolu, M.[Murali], Lee, H.L.[Hong-Lak], Savarese, S.[Silvio],
An efficient branch-and-bound algorithm for optimal human pose estimation,
CVPR12(1616-1623).
IEEE DOI 1208
BibRef

Simo-Serra, E.[Edgar], Quattoni, A.[Ariadna], Torras, C.[Carme], Moreno-Noguer, F.[Francesc],
A Joint Model for 2D and 3D Pose Estimation from a Single Image,
CVPR13(3634-3641)
IEEE DOI 1309
BibRef

Moreno-Noguer, F.[Francesc],
3D Human Pose Estimation from a Single Image via Distance Matrix Regression,
CVPR17(1561-1570)
IEEE DOI 1711
Detectors, Euclidean distance, Pose estimation, Shape, Training, BibRef

Simo-Serra, E., Ramisa, A., Alenya, G., Torras, C.[Carme], Moreno-Noguer, F.[Francesc],
Single image 3D human pose estimation from noisy observations,
CVPR12(2673-2680).
IEEE DOI 1208
BibRef

Sun, M.[Min], Kohli, P.[Pushmeet], Shotton, J.J.D.[Jamie J.D.],
Conditional regression forests for human pose estimation,
CVPR12(3394-3401).
IEEE DOI 1208
BibRef

Souvenir, R.[Richard], Hajja, A.[Ayman], Spurlock, S.[Scott],
Gamesourcing to acquire labeled human pose estimation data,
CVCG12(1-6).
IEEE DOI 1207
BibRef

Akhtar, S., Ahmad, A.R., Abdel-Rahman, E.M.,
A Metaheuristic Bat-Inspired Algorithm for Full Body Human Pose Estimation,
CRV12(369-375).
IEEE DOI 1207
BibRef

Gong, W.J.[Wen-Juan], Brauer, J.[Jurgen], Arens, M.[Michael], Gonzalez, J.[Jordi],
Modeling vs. learning approaches for monocular 3D human pose estimation,
PEAction11(1287-1294).
IEEE DOI 1201
BibRef
And: A2, A1, A4, A3:
On the effect of temporal information on monocular 3d human pose estimation,
ARTEMIS11(906-913).
IEEE DOI 1201
See also Voting Strategies for Anatomical Landmark Localization Using the Implicit Shape Model. BibRef

Holt, B.[Brian], Ong, E.J.[Eng-Jon], Bowden, R.[Richard],
Accurate static pose estimation combining direct regression and geodesic extrema,
FG13(1-7)
IEEE DOI 1309
differential geometry BibRef

Holt, B.[Brian], Ong, E.J.[Eng-Jon], Cooper, H.[Helen], Bowden, R.[Richard],
Putting the pieces together: Connected Poselets for human pose estimation,
ConDepth11(1196-1201).
IEEE DOI 1201
BibRef

Chen, K.[Ke], Gong, S.G.[Shao-Gang], Xiang, T.[Tao],
Human Pose Estimation Using Structural Support Vector Machines,
SISM11(846-851).
IEEE DOI 1201
See also Support Vector Machine Based Multi-View Face Detection and Recognition. BibRef

Richter, M.[Michal], Varanasi, K.[Kiran], Hasler, N.[Nils], Theobalt, C.[Christian],
Real-Time Reshaping of Humans,
3DIMPVT12(340-347).
IEEE DOI 1212
BibRef

Müller, J.[Jürgen], Arens, M.[Michael],
Human pose estimation with implicit shape models,
ARTEMIS10(9-14).
DOI Link 1111
BibRef

Han, H.[Hong], Tong, M.L.[Ming-Lei], Gou, J.X.[Jing-Xiang], Wang, R.[Rui], Feng, G.J.[Guang-Jie],
Discriminative Human Pose Estimation Based on the Bandelet2 Image Descriptor,
ICIG11(679-684).
IEEE DOI 1109
BibRef

Wang, Y.[Yang], Tran, D.[Duan], Liao, Z.C.[Zi-Cheng],
Learning hierarchical poselets for human parsing,
CVPR11(1705-1712).
IEEE DOI 1106
BibRef

Hara, K.[Kota], Kurokawa, T.[Takaharu],
Human pose estimation using patch-based candidate generation and model-based verification,
FG11(687-693).
IEEE DOI 1103
BibRef

Hara, K.[Kota],
Real-time inference of 3D human poses by assembling local patches,
WACV09(1-8).
IEEE DOI 0912
BibRef

Park, J.H.[Jung-Hwa], Karungaru, S.[Stephen], Terada, K.[Kenji],
Recognition of a person's state using FG Vision Sensor,
FCV11(1-4).
IEEE DOI 1102
3-D sensor. BibRef

Park, A.[Anjin], Jung, K.C.[Kee-Chul],
Human Pose Recognition Using Chamfer Distance in Reduced Background Edge for Human-Robot Interaction,
ISVC10(II: 726-735).
Springer DOI 1011
BibRef

Flitti, F., Bennamoun, M., Huynh, D.Q., Owens, R.A.,
Probabilistic human pose recovery from 2D images,
ICIP10(1517-1520).
IEEE DOI 1009
BibRef

Fihl, P., Moeslund, T.B.,
Pose Estimation of Interacting People using Pictorial Structures,
AVSS10(462-468).
IEEE DOI 1009
BibRef

Hur, D.C.[Dong-Cheol], Wallraven, C.[Christian], Lee, S.W.[Seong-Whan],
View Invariant Body Pose Estimation Based on Biased Manifold Learning,
ICPR10(3866-3869).
IEEE DOI 1008
BibRef

Wang, Y.K.[Yuan-Kai], Cheng, K.Y.[Kuang-You],
3D Human Pose Estimation by an Annealed Two-Stage Inference Method,
ICPR10(535-538).
IEEE DOI 1008
BibRef

Boughorbel, S.[Sabri], Bruekers, F.[Fons], Breebaart, J.[Jeroen],
Baby-Posture Classification from Pressure-Sensor Data,
ICPR10(556-559).
IEEE DOI 1008
BibRef

Singh, V.K.[Vivek Kumar], Khan, F.M.[Furqan Muhammad], Nevatia, R.[Ram],
Multiple pose context trees for estimating human pose in object context,
SMiCV10(17-24).
IEEE DOI 1006
See also Simultaneous inference of activity, pose and object. BibRef

Huang, J.B.[Jia-Bin], Yang, M.H.[Ming-Hsuan],
Estimating Human Pose from Occluded Images,
ACCV09(I: 48-60).
Springer DOI 0909
BibRef

Guo, W.W.[Wei-Wei], Patras, I.[Ioannis],
Learning Output-kernel-dependent Regression for Human Pose Estimation,
BMVCWS10(xx-yy).
HTML Version. 1009
BibRef
Earlier:
Discriminative 3D human pose estimation from monocular images via topological preserving hierarchical affinity clustering,
S3DV09(9-15).
IEEE DOI 0910
BibRef

Pehlivan, S.[Selen], Duygulu, P.[Pinar],
3D human pose search using oriented cylinders,
S3DV09(16-22).
IEEE DOI 0910
BibRef

Shahbudin, S., Hussain, A., El-Shafie, A.[Ahmed], Tahir, N.M., Samad, S.A.,
Adaptive-Neuro Fuzzy Inference System for Human Posture Classification Using a Simplified Shock Graph,
IVIC09(585-595).
Springer DOI 0911
BibRef

Cheng, P.[Peng], Li, W.Q.[Wan-Qing], Ogunbona, P.[Philip],
Kernel PCA of HOG features for posture detection,
IVCNZ09(415-420).
IEEE DOI 0911
See also Head pose estimation based on extended non-negative matrix factorization. BibRef

Ben Abdelkader, C.[Chiraz], Yacoob, Y.[Yaser],
Statistical body height estimation from a single image,
FG08(1-7).
IEEE DOI 0809
BibRef

Chen, Y.[Yan], Wu, Q.A.[Qi-Ang], He, X.J.[Xiang-Jian], Du, C.H.[Chun-Hua], Yang, J.[Jie],
Extracting key postures using radon transform,
IVCNZ08(1-5).
IEEE DOI 0811
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Onishi, K.[Katsunori], Takiguchi, T.[Tetsuya], Ariki, Y.[Yasuo],
3D human posture estimation using the HoG features from monocular image,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Kamiya, K.[Kazuhiro], Kudo, M.[Mineichi], Nonaka, H.[Hidetoshi], Toyama, J.[Jun],
Sitting posture analysis by pressure sensors,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Aubry, M.[Matthieu], Julliard, F.[Frédéric], Gibet, S.[Sylvie],
The Ergonomic Analysis of the Workplace of Physically Disabled Individuals,
GW07(255-260).
Springer DOI 0705
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Baranda, J.[Jorge], Jeanne, V.[Vincent], Braspenning, R.[Ralph],
Efficiency improvement of human body detection with histograms of oriented gradients,
ICDSC08(1-9).
IEEE DOI 0809
BibRef

Bandouch, J., Engstler, F., Beetz, M.,
Evaluation of Hierarchical Sampling Strategies in 3D Human Pose Estimation,
BMVC08(xx-yy).
PDF File. 0809
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Daubney, B.[Ben], Xie, X.H.[Xiang-Hua],
Entropy Driven Hierarchical Search for 3D Human Pose Estimation,
BMVC11(xx-yy).
HTML Version. 1110
BibRef
Earlier:
Estimating 3D Human Pose from Single Images Using Iterative Refinement of the Prior,
ICPR10(3440-3443).
IEEE DOI 1008
BibRef
And:
Estimating 3D Pose via Stochastic Search and Expectation Maximization,
AMDO10(67-77).
Springer DOI 1007
BibRef

Urtasun, R.[Raquel], Darrell, T.J.[Trevor J.],
Sparse probabilistic regression for activity-independent human pose inference,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Gupta, A.[Abhinav], Chen, T.[Trista], Chen, F.[Francine], Kimber, D.[Don], Davis, L.S.[Larry S.],
Context and observation driven latent variable model for human pose estimation,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Zhu, L.L.[Long Leo], Chen, Y.H.[Yuan-Hao], Lu, Y.F.[Yi-Fei], Lin, C.X.[Chen-Xi], Yuille, A.L.[Alan L.],
Max Margin AND/OR Graph learning for parsing the human body,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Liu, X.M.[Xiao-Ming], Yu, T.[Ting], Sebastian, T.[Thomas], Tu, P.H.[Peter H.],
Boosted deformable model for human body alignment,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Wang, Y.[Yi], Qian, G.[Gang],
Robust Human Pose Recognition Using Unlabelled Markers,
WACV08(1-7).
IEEE DOI 0801
BibRef

Morita, S.[Satoru],
Generating Body Surface Deformation Using Level Set Method,
AMFG07(84-95).
Springer DOI 0710
BibRef

Srinivasan, P.[Praveen], Shi, J.B.[Jian-Bo],
Bottom-Up Recognition and Parsing of the Human Body,
CVPR07(1-8).
IEEE DOI 0706
BibRef
And: EMMCVPR07(153-168).
Springer DOI 0708
BibRef

Pham, Q.C.[Quoc-Cuong], Gond, L.[Laetitia], Begard, J.[Julien], Allezard, N.[Nicolas], Sayd, P.[Patrick],
Real-Time Posture Analysis in a Crowd using Thermal Imaging,
VS07(1-8).
IEEE DOI 0706
BibRef

Okada, R.[Ryuzo], Soatto, S.[Stefano],
Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images,
ECCV08(II: 434-445).
Springer DOI 0810
See also Hybrid Dynamical Models of Human Motion for the Recognition of Human Gaits. BibRef

Menier, C.[Clement], Boyer, E.[Edmond], Raffin, B.[Bruno],
3D Skeleton-Based Body Pose Recovery,
3DPVT06(389-396).
IEEE DOI 0606
BibRef

Robertson, C., Trucco, E.,
Human Body Posture via Hierarchical Evolutionary Optimization,
BMVC06(III:999).
PDF File. 0609
BibRef

Chen, Y.P.[Yin-Peng], Sundaram, H.[Hari], James, J.[Jodi],
Estimating the Physical Effort of Human Poses,
CIVR06(487-490).
Springer DOI 0607
BibRef

Navaratnam, R.[Ramanan], Fitzgibbon, A.W.[Andrew W.], Cipolla, R.[Roberto],
The Joint Manifold Model for Semi-supervised Multi-valued Regression,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Navaratnam, R.[Ramanan], Fitzgibbon, A.W.[Andrew W.],
Semi-supervised Learning of Joint Density Models for Human Pose Estimation,
BMVC06(II:79).
PDF File. 0609
BibRef

Castiello, C., d'Orazio, T., Fanelli, A.M., Spagnolo, P., Torsello, M.A.,
A model-free approach for posture classification,
AVSBS05(276-281).
IEEE DOI 0602
BibRef

Lan, X.Y.[Xiang-Yang], Huttenlocher, D.P.[Daniel P.],
Beyond Trees: Common-Factor Models for 2D Human Pose Recovery,
ICCV05(I: 470-477).
IEEE DOI 0510
BibRef

Hua, G.[Gang], Yang, M.H.[Ming-Hsuan], Wu, Y.[Ying],
Learning to Estimate Human Pose with Data Driven Belief Propagation,
CVPR05(II: 747-754).
IEEE DOI 0507
BibRef

Nakajima, C.,
Posture recognition of nuclear power plant operators by supervised learning,
ICIP04(II: 877-880).
IEEE DOI 0505
BibRef

Mota, S.[Selene], and Picard, R.W.[Rosalind W.],
Automated Posture Analysis for detecting Learner's Interest Level,
Vismod-TR574, June 2003
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Shakhnarovich, G.[Gregory], Viola, P.A.[Paul A.], Darrell, T.J.[Trevor J.],
Fast Pose Estimation with Parameter-Sensitive Hashing,
ICCV03(750-757).
IEEE DOI 0311
BibRef
And: MIT AIMAIM-2003-009, April 18, 2003.
WWW Link. learns a set of hashing functions that efficiently index examples relevant to a particular estimation task. 0306
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Azimi-Sadjadi, M.R.,
Consistency and coupling in human model likelihoods,
AFGR02(22-27).
IEEE DOI 0206
BibRef

Demirdjian, D.[David], Urtasun, R.[Raquel],
Patch-Based Pose Inference with a Mixture of Density Estimators,
AMFG07(96-108).
Springer DOI 0710
BibRef

Njĺstad, J., Grinaker, S., Storhaug, G.A.,
Estimating Parameters in a 2 1/2 D human model,
SCIA99(Computer Vision I). BibRef 9900

Koutamanis, A., Mitossi, V.,
On the Recognition of Posture,
ICPR92(I:542-545).
IEEE DOI BibRef 9200

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Multi-Person Human Pose Desicriptions .


Last update:Oct 19, 2020 at 15:02:28