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REFERENCES
1. Dumas RP, Vella MA, Hatchimonji JS, Ma L, Maher Z, Holena DN. Trauma video review utilization: a survey of practice in the
United States. Am J Surg 2020;219:49-53. DOI PubMed PMC
2. Lynch RJ, Englesbe MJ, Sturm L, et al. Measurement of foot traffic in the operating room: implications for infection control. Am J
Med Qual 2009;24:45-52. DOI PubMed
3. Hazlehurst B, McMullen CK, Gorman PN. Distributed cognition in the heart room: how situation awareness arises from coordinated
communications during cardiac surgery. J Biomed Inform 2007;40:539-51. DOI PubMed
4. Harders M, Malangoni MA, Weight S, Sidhu T. Improving operating room efficiency through process redesign. Surgery
2006;140:509-14. DOI PubMed
5. Palmer G 2nd, Abernathy JH 3rd, Swinton G, et al. Realizing improved patient care through human-centered operating room design: a
human factors methodology for observing flow disruptions in the cardiothoracic operating room. Anesthesiology 2013;119:1066-77.
DOI PubMed
6. Catchpole K, Mishra A, Handa A, McCulloch P. Teamwork and error in the operating room: analysis of skills and roles. Ann Surg
2008;247:699-706. DOI PubMed
7. Mottaghi A, Sharghi A, Yeung S, Mohareri O. Adaptation of surgical activity recognition models across operating rooms. In: Wang L,
Dou Q, Fletcher PT, Speidel S, Li S, editors. Medical image computing and computer assisted intervention - MICCAI 2022. Cham:
Springer; 2022. pp. 530-40. DOI
8. Bogo F, Kanazawa A, Lassner C, Gehler P, Romero J, Black MJ. Keep it SMPL: automatic estimation of 3D human pose and shape
from a single image. In: Leibe B, Matas J, Sebe N, Welling M, editors. Computer Vision - ECCV 2016. Cham: Springer; 2016. pp.
561-78. DOI
9. Li H, Zech J, Hong D, Ghamisi P, Schultz M, Zipf A. Leveraging OpenStreetMap and multimodal remote sensing data with joint deep
learning for wastewater treatment plants detection. Int J Appl Earth Obs Geoinf 2022;110:102804. DOI PubMed PMC
10. Yuan Y, Iqbal U, Molchanov P, Kitani K, Kautz J. GLAMR: Global occlusion-aware human mesh recovery with dynamic cameras. In:
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2022. pp. 11038-49. Available from:
https://openaccess.thecvf.com/content/CVPR2022/html/Yuan_GLAMR_Global_Occlusion-Aware_Human_Mesh_Recovery_With_
Dynamic_Cameras_CVPR_2022_paper.html. [Last accessed on 21 Jun 2024].
11. Kocabas M, Athanasiou N, Black MJ. Vibe: Video inference for human body pose and shape estimation. In: Proceedings of the IEEE/
CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2020. pp. 5253-63. Available from: https://openaccess.thecvf.
com/content_CVPR_2020/html/Kocabas_VIBE_Video_Inference_for_Human_Body_Pose_and_Shape_Estimation_CVPR_2020_
paper.html. [Last accessed on 21 Jun 2024].
12. Tian Y, Zhang H, Liu Y, Wang L. Recovering 3D human mesh from monocular images: a survey. IEEE Trans Pattern Anal Mach
Intell 2023;45:15406-25. DOI
13. Shao S, Zhao Z, Li B, et al. CrowdHuman: a benchmark for detecting human in a crowd. arXiv. [Preprint.] Apr 30, 2018 [accessed
2024 Jun 21]. Available from: https://arxiv.org/abs/1805.00123.
14. Weng SK, Kuo CM, Tu SK. Video object tracking using adaptive Kalman filter. J Vis Commun Image Represent 2006;17:1190-208.
DOI
15. Li Z, Liu J, Zhang Z, Xu S, Yan Y. CLIFF: carrying location information in full frames into human pose and shape estimation. In:
Avidan S, Brostow G, Cissé M, Farinella GM, Hassner T, editors. Computer Vision - ECCV 2022: 17th European Conference; 2022
Oct 23-27; Tel Aviv, Israel. Cham: Springer; 2022. pp. 590-606. DOI
16. Kolotouros N, Pavlakos G, Black MJ, Daniilidis K. Learning to reconstruct 3D human pose and shape via model-fitting in the loop. In:
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). 2019. pp. 2252-61. Available from: https://
openaccess.thecvf.com/content_ICCV_2019/html/Kolotouros_Learning_to_Reconstruct_3D_Human_Pose_and_Shape_via_Model-
Fitting_ICCV_2019_paper.html. [Last accessed on 21 Jun 2024].
17. Lin TY, Maire M, Belongie S, et al. Microsoft COCO: common objects in context. In: Fleet D, Pajdla T, Schiele B, Tuytelaars T,
editors. In: Computer Vision - ECCV 2014. Cham: Springer; 2014. pp. 740-55. DOI
18. Ionescu C, Papava D, Olaru V, Sminchisescu C. Human3.6M: large scale datasets and predictive methods for 3D human sensing in
natural environments. IEEE Trans Pattern Anal Mach Intell 2014;36:1325-39. DOI PubMed
19. 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. In: Ferrari V, Hebert M, Sminchisescu C, Weiss Y, editors. Computer Vision - ECCV 2018. Cham: Springer; 2018.
pp. 614-31. DOI
20. Redmon J, Divvala S, Girshick R, Farhadi A. You only look once: unified, real-time object detection. In: Proceedings of the IEEE
Conference on Computer Vision and Pattern Recognition (CVPR); 2016. pp. 779-88. Available from: https://www.cv-foundation.org/
openaccess/content_cvpr_2016/html/Redmon_You_Only_Look_CVPR_2016_paper.html. [Last accessed on 21 Jun 2024].
21. Pavlakos G, Choutas V, Ghorbani N, et al. Expressive body capture: 3D hands, face, and body from a single image. In: Proceedings of
the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR); 2019. pp. 10975-85. Available from: https://

