Monocular 3D Human Pose Estimation for REBA Ergonomics: A Critical Review of Recent Advances

1. A review of deep learning techniques for 2D and 3D human pose estimation10.1016/j.imavis.2021.104282 ↗

2. Nguyen TD, Kresovic M. A survey of top-down approaches for human pose estimation. arXiv:2202.02656. 2022.

3. A survey on model based approaches for 2D and 3D visual human pose recovery10.3390/s140304189 ↗

4. Monocular human pose estimation: a survey of deep learning-based methods10.1016/j.cviu.2019.102897 ↗

5. Deep learning based 2D human pose estimation: a survey10.26599/TST.2018.9010100 ↗

6. A kinect-based workplace postural analysis system using deep residual networks

7. Ergonomic risk prediction for awkward postures from 3D keypoints using deep learning10.1109/ACCESS.2023.3324659 ↗

8. Validation of computer vision-based ergonomic risk assessment tools for real manufacturing environments10.1038/s41598-024-79373-4 ↗

9. Risk assessment of musculoskeletal disorders by OVAKO Working posture Analysis System OWAS and evaluate the effect of ergonomic training on posture of farmers

10. An observational method for Postural Ergonomic Risk Assessment (PERA)10.1016/j.ergon.2016.11.007 ↗

11. Intuitionistic fuzzy REBA method and its application in a manufacturing company

12. Design of an ergonomic App for entire rapid body assessment based on Mask RCNN

13. A new scoring system for the Rapid Entire Body Assessment (REBA) based on fuzzy sets and Bayesian networks10.1016/j.ergon.2020.103058 ↗

14. Wearable devices for ergonomics: a systematic literature review10.3390/s21030777 ↗

15. Clustered pose and nonlinear appearance models for human pose estimation

16. Learning effective human pose estimation from inaccurate annotation

17. Andriluka M, Pishchulin L. 2D human pose estimation: new benchmark and state of the art analysis [Internet]. [cited 2025 Feb 10]. Available from: http://openaccess.thecvf.com/content_cvpr_2014/html/Andriluka_2D_Human_Pose_2014_CVPR_paper.html.10.1109/CVPR.2014.471 ↗

18. Microsoft COCO: common objects in context

19. HumanEva: synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion10.1007/s11263-009-0273-6 ↗

20. Human3.6M: large scale datasets and predictive methods for 3D human sensing in natural environments10.1109/TPAMI.2013.248 ↗

21. Panoptic studio: a massively multiview system for social interaction capture10.1109/TPAMI.2017.2782743 ↗

22. Monocular 3D human pose estimation in the wild using improved CNN supervision

23. Total capture: 3D human pose estimation fusing video and inertial sensors

24. von Marcard T, Henschel R, Black MJ, Rosenhahn B, Pons-Moll G. Recovering accurate 3D human pose in the wild using IMUs and a moving camera [Internet]. [cited 2025 Feb 10]. Available from: http://virtualhumans.mpi-inf.mpg.de/3DPW.

25. Mehta D, Sotnychenko O. Single-shot multi-person 3D pose estimation from monocular RGB [Internet]. [cited 2025 Feb 10]. Available from: https://ieeexplore.ieee.org/abstract/document/8490962/.

26. Learning from Synthetic Humans

27. Ebadi SE, Jhang YC, Zook A, Dhakad S, Crespi A, Parisi P, et al. PeopleSansPeople: a synthetic data generator for human-centric computer vision [Internet]. [cited 2025 Feb 10]. Available from: https://arxiv.org/abs/2112.09290v2.

28. Zhou X, Huang Q, Sun X, Xue X, Wei Y. Towards 3D human pose estimation in the wild: a weakly-supervised approach [Internet]. [cited 2025 Feb 10]. Available from: https://github.com/.

29. Orthographic projection linear regression for single image 3D human pose estimation

30. Classification of human body parts using histogram of oriented gradients

31. Estimation of 3D human pose using prior knowledge10.1117/1.JEI.30.4.040502 ↗

32. Compositional human pose regression

33. Tompson J, Jain A, LeCun Y, Bregler C. Joint training of a convolutional network and a graphical model for human pose estimation [Internet]; 2014. [cited 2025 Feb 10]. Available from: https://arxiv.org/abs/1406.2984v2.

34. Human pose estimation using deep consensus voting

35. Convolutional pose machines

36. Human pose estimation via convolutional part heatmap regression

37. Stacked hourglass networks for human pose estimation

38. Coarse-to-fine volumetric prediction for single-image 3D human pose

39. Integral human pose regression

40. Sun K, Xiao B, Liu D. IEEE JWP of the, 2019 undefined. Deep high-resolution representation learning for human pose estimation [Internet]. [cited 2025 Feb 10]. Available from: http://openaccess.thecvf.com/content_CVPR_2019/html/Sun_Deep_HighResolution_Representation_Learning_for_Human_Pose_Estimation_CVPR_2019_paper.html.10.1109/CVPR.2019.00584 ↗

41. EfficientPose: scalable single-person pose estimation10.1007/s10489-020-01918-7 ↗

42. Estimating human body configurations using shape context matching

43. 3D human pose from silhouettes by relevance vector regression

44. 3D human posture estimation using the HOG features from monocular image

45. Diffusion-Based 3D human pose estimation with multi-hypothesis aggregation

46. Metaxas DiN. Semantic graph convolutional networks for 3D human pose regression

47. Latent structured models for human pose estimation

48. 3D human pose estimation via intuitive physics

49. Neural monocular 3D human motion capture with physical awareness10.1145/3450626.3459825 ↗

50. Lifting from the deep: convolutional 3D pose estimation from a single image

51. Simple baselines for human pose estimation

52. Context modeling in 3D human pose estimation: a unified perspective

53. Maximum-margin structured learning with deep networks for 3D human pose estimation

54. Learning camera viewpoint using CNN to improve 3D body pose estimation

55. Human pose as calibration pattern: 3D human pose estimation with multiple unsynchronized and uncalibrated cameras

56. Probabilistic triangulation for uncalibrated multi-view 3D human pose estimation

57. Direct multi-view multi-person 3D pose estimation. In: advances in neural information processing systems

58. Uncertainty-aware adaptation for self-supervised 3D human pose estimation

59. SSP-Net: scalable sequential pyramid networks for real-time 3D human pose regression10.1016/j.patcog.2023.109714 ↗

60. Recovering 3D human body configurations using shape contexts10.1109/TPAMI.2006.149 ↗

61. Lifting 2D human pose to 3D: a weakly supervised approach

62. 3D human pose estimation from monocular images with deep convolutional neural network

63. CameraPose: weakly-supervised monocular 3D human pose estimation by leveraging in-the-wild 2D annotations

64. Sparse representation for 3D shape estimation: a convex relaxation approach10.1109/TPAMI.2016.2605097 ↗

65. A dual-source approach for 3D pose estimation from a single image

66. Consensus-based optimization for 3D human pose estimation in camera coordinates10.1007/s11263-021-01570-9 ↗

67. Marker-less 3D human motion capture with monocular image sequence and height-maps. In: Lecture Notes in Computer Science

68. 3D human pose estimation from a single image via distance matrix regression

69. A simple yet effective baseline for 3D human pose estimation

70. Wang M, Chen X, Liu W, Qian C, Lin L, Ma L. Drpose3D: depth ranking in 3D human pose estimation. arXiv:1805.08973. 2018.10.24963/ijcai.2018/136 ↗

71. HEMlets pose: learning part-centric heatmap triplets for accurate 3D human pose estimation

72. An improved mixture density network for 3D human pose estimation with ordinal ranking

73. Pose2Mesh: graph convolutional network for 3D human pose and mesh recovery from a 2D human pose

74. Zhao W, Tian Y, Ye Q, Jiao J, Wang W. GraFormer: graph convolution transformer for 3D pose estimation [Internet]. [cited 2025 Feb 10]. Available from: http://arxiv.org/abs/2109.08364.

75. Modulated graph convolutional network for 3D human pose estimation

76. DiffuPose: monocular 3D human pose estimation via denoising diffusion probabilistic model

77. Deep kinematic pose regression. Lecture Notes in Computer Science

78. Deep kinematics analysis for monocular 3D human pose estimation

79. Habibie I, Xu W, Mehta D, Pons-Moll G, Theobalt C. In the wild human pose estimation using explicit 2D features and intermediate 3D representations [Internet]. [cited 2025 Feb 10]. Available from: http://openaccess.thecvf.com/content_CVPR_2019/html/Habibie_In_the_Wild_Human_Pose_Estimation_Using_Explicit_2D_Features_CVPR_2019_paper.html.10.1109/CVPR.2019.01116 ↗

80. Chen CH, Tyagi A, Agrawal A, Drover D, Mv R, Stojanov S, et al. Unsupervised 3D pose estimation with geometric self-supervision [Internet]. [cited 2025 Feb 10]. Available from: http://openaccess.thecvf.com/content_CVPR_2019/html/Chen_Unsupervised_3D_Pose_Estimation_With_Geometric_Self-Supervision_CVPR_2019_paper.html.10.1109/CVPR.2019.00586 ↗

81. ElePose: unsupervised 3D human pose estimation by predicting camera elevation and learning normalizing flows on 2D poses

82. Abdollahzade F, Mohammadi F. Working posture and its predictors in hospital operating room nurses [Internet]. [cited 2025 Feb 10]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4847110/.

83. Chen J, Qiu J. Construction worker’s awkward posture recognition through supervised motion tensor decomposition. nurses [Internet]. [cited 2025 Feb 10]. Available from: https://www.sciencedirect.com/science/article/pii/S0926580517300651.

84. Ergonomics study on an assembly line used in the automotive industry

85. Automated postural ergonomic risk assessment using vision-based posture classification10.1016/j.autcon.2021.103725 ↗

86. Automatic clustering of proper working postures for phases of movement10.1016/j.autcon.2022.104223 ↗

87. CREBAS: computer-based REBA evaluation system for wood manufacturers using MediaPipe10.3390/app13020938 ↗

88. Development of ergonomic posture recognition technique based on 2D ordinary camera for construction hazard prevention through view-invariant features in 2D skeleton motion10.1016/j.aei.2017.11.001 ↗

89. Automatic ergonomic risk assessment using a variational deep network architecture

90. Ergonomic postural assessment using a new open-source human pose estimation technology (OpenPose)10.1016/j.ergon.2021.103164 ↗

91. Ergonomic risk assessment based on computer vision and machine learning10.1016/j.cie.2020.106816 ↗

92. Ergonomic risk assessment of smartphone users using the Rapid Upper Limb Assessment (RULA) tool10.1371/journal.pone.0203394 ↗

93. A deep learning-based RULA method for working posture assessment10.1177/1071181319631174 ↗

94. Development of a fully automated RULA assessment system based on computer vision10.1016/j.ergon.2021.103218 ↗

95. RGB-D ergonomic assessment system of adopted working postures10.1016/j.apergo.2019.05.004 ↗

96. A novel method of human joint prediction in an occlusion scene by using low-cost motion capture technique10.3390/s20041119 ↗