[1] Ankur Agarwal and Bill Triggs. Recovering 3d human pose from monocular images. IEEE transactions on pattern analysis and machine intelligence, 28(1):44–58, 2005.
[2] Robert Behrendt, Amir M Ghaznavi, Meredith Mahan, Susan Craft, and Aamir Siddiqui. Continuous bedside pressure mapping and rates of hospital-associated pressure ulcers in
a medical intensive care unit. American Journal of Critical Care, 23(2):127–133, 2014.
[3] Dan Berlowitz, C VanDeusen Lukas, V Parker, A Niederhauser, J Silver, C Logan, and E Ayello. Preventing pressure ulcers in hospitals: a toolkit for improving quality of care. Agency for Healthcare Research and Quality, 2011.
[4] Joyce M Black, Janet E Cuddigan, Maralyn A Walko, L Alan Didier, Maria J Lander, and Maureen R Kelpe. Medical device related pressure ulcers in hospitalized patients. International wound journal, 7(5):358–365, 2010.
[5] Ching-Hang Chen, Ambrish Tyagi, Amit Agrawal, Dylan Drover, Rohith Mv, Stefan Stojanov, and James M Rehg. Unsupervised 3d pose estimation with geometric selfsupervision. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 5714–5724, 2019
[6] Vasileios Choutas, Lea Muller, Chun-Hao P Huang, Siyu Tang, Dimitrios Tzionas, and Michael J Black. Accurate 3d body shape regression using metric and semantic attributes.
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 2718–2728, 2022. 6
[7] Henry M Clever, Ariel Kapusta, Daehyung Park, Zackory Erickson, Yash Chitalia, and Charles C Kemp. 3d human pose estimation on a configurable bed from a pressure image. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 54–61. IEEE, 2018
[8] Henry M Clever, Zackory Erickson, Ariel Kapusta, Greg Turk, Karen Liu, and Charles C Kemp. Bodies at rest: 3d human pose and shape estimation from a pressure image using synthetic data. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 6215–6224, 2020. 3
[9] Henry M Clever, Patrick L Grady, Greg Turk, and Charles C Kemp. Bodypressure-inferring body pose and contact pressure from a depth image. IEEE Transactions on Pattern
Analysis and Machine Intelligence, 45(1):137–153, 2022.
[10] Mihai Fieraru, Mihai Zanfir, Elisabeta Oneata, Alin-Ionut Popa, Vlad Olaru, and Cristian Sminchisescu. Learning complex 3d human self-contact. In Proceedings of the AAAI Conference on Artificial Intelligence, pages 1343–1351, 2021
[11] Gheorghita Ghinea, Fotis Spyridonis, Tacha Serif, and Andrew O Frank. 3-d pain drawings—mobile data collection using a pda. IEEE Transactions on information technology in biomedicine, 12(1):27–33, 2008
[12] Xuan Gong, Meng Zheng, Benjamin Planche, Srikrishna Karanam, Terrence Chen, David Doermann, and Ziyan Wu. Self-supervised human mesh recovery with cross representation alignment. In European Conference on Computer Vision, pages 212–230. Springer, 2022. 3
[13] Lena Gunningberg, Ulrika Poder, and Cheryl Carli. Facilitating student nurses’ learning by real time feedback of positioning to avoid pressure ulcers: evaluation of clinical simulation. J Nurs Educ Practice, 6(1):1–8, 2016.
[14] Mohamed Hassan, Vasileios Choutas, Dimitrios Tzionas, and Michael J Black. Resolving 3d human pose ambiguities with 3d scene constraints. In Proceedings of the IEEE/CVF international conference on computer vision, pages 2282–2292, 2019.
[15] Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern
recognition, pages 770–778, 2016.
[16] Thomas Holleczek, Alex Ruegg, Holger Harms, and Gerhard Troster. Textile pressure sensors for sports applications. In SENSORS, 2010 IEEE, pages 732–737, 2010.
[17] Lisa Hultin, Estrid Olsson, Cheryl Carli, and Lena Gunningberg. Pressure mapping in elderly care. Journal of Wound, Ostomy and Continence Nursing, 44(2):142–147, 2017.
[18] Debra Jackson, Ahmed M Sarki, Ria Betteridge, and Joanne Brooke. Medical device-related pressure ulcers: a systematic review and meta-analysis. International journal of nursing studies, 92:109–120, 2019.
[19] Angjoo Kanazawa, Michael J Black, David W Jacobs, and Jitendra Malik. End-to-end recovery of human shape and pose. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 7122–7131, 2018.
[20] Susan A Kayser, Catherine A VanGilder, Elizabeth A Ayello, and Charlie Lachenbruch. Prevalence and analysis of medical device-related pressure injuries: results from the international pressure ulcer prevalence survey. Advances in skin & wound care, 31(6):276, 2018.
[21] Diederik P Kingma and Jimmy Ba. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980, 2014.
[22] Muhammed Kocabas, Salih Karagoz, and Emre Akbas. Selfsupervised learning of 3d human pose using multi-view geometry. In Proceedings of the IEEE/CVF conference on
computer vision and pattern recognition, pages 1077–1086, 2014
[23] Nikos Kolotouros, Georgios Pavlakos, Michael J Black, and Kostas Daniilidis. 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, pages 2252–2261, 2019.
[24] Shichao Li, Lei Ke, Kevin Pratama, Yu-Wing Tai, Chi-Keung Tang, and Kwang-Ting Cheng. Cascaded deep monocular 3d human pose estimation with evolutionary training data. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 6173–6183, 2020.
[25] Kevin Lin, Lijuan Wang, and Zicheng Liu. End-to-end human pose and mesh reconstruction with transformers. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 1954–1963, 2021. 3
[26] Shuangjun Liu and Sarah Ostadabbas. Seeing under the cover: A physics guided learning approach for in-bed pose estimation. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 236–2014. Springer, 2019.
[27] Shuangjun Liu and Sarah Ostadabbas. Pressure eye: In-bed contact pressure estimation via contact-less imaging. Medical Image Analysis, 87:102835, 2023.
[28] Shuangjun Liu, Xiaofei Huang, Nihang Fu, Cheng Li, Zhongnan Su, and Sarah Ostadabbas. Simultaneously collected multimodal lying pose dataset: Enabling in-bed human pose monitoring. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(1):1106–1118, 2022.
[29] Wu Liu, Qian Bao, Yu Sun, and Tao Mei. Recent advances of monocular 2d and 3d human pose estimation: A deep learning perspective. ACM Computing Surveys, 55(4):1–41, 2022.
[30] Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J Black. Smpl: A skinned multiperson linear model. In Seminal Graphics Papers: Pushing
the Boundaries, Volume 2, pages 851–866. 2023.
[31] Sam Mansfield, Katia Obraczka, and Shuvo Roy. Pressure injury prevention: A survey. IEEE Reviews in Biomedical Engineering, 13:352–368, 2020. 1, 6
[32] Danielle M Minteer, Patsy Simon, Donald P Taylor, Wenyan Jia, Yuecheng Li, Mingui Sun, and J Peter Rubin. Pressure ulcer monitoring platform—a prospective, human subject clinical study to validate patient repositioning monitoring device to prevent pressure ulcers. Advances in wound care, 9(1):28–33, 2020. 1
[33] Lea Muller, Ahmed AA Osman, Siyu Tang, Chun-Hao P Huang, and Michael J Black. On self-contact and human pose. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 9990–9999, 2014.
[34] Alejandro Newell, Kaiyu Yang, and Jia Deng. Stacked hourglass networks for human pose estimation. In Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII 14, pages 483–499. Springer, 2016. 3
[35] Kaichiro Nishi and Jun Miura. Generation of human depth images with body part labels for complex human pose recognition. Pattern Recognition, 71:402–413, 2017. 2
[36] Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani,Timo Bolkart, Ahmed AA Osman, Dimitrios Tzionas, and Michael J Black. 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, pages 10975–10985, 2019. 3
[37] Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas. Pointnet: Deep learning on point sets for 3d classification and segmentation. In Proceedings of the IEEE conference
on computer vision and pattern recognition, pages 652–660, 2014.
[38] Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas. Pointnet++: Deep hierarchical feature learning on point sets in a metric space. Advances in neural information
processing systems, 30, 2017. 4
[39] Ronald G Scott and Kristen M Thurman. Visual feedback of continuous bedside pressure mapping to optimize effective patient repositioning. Advances in wound care, 3(5):376–382, 2014. 1
[40] Devdip Sen, John McNeill, Yitzhak Mendelson, Raymond Dunn, and Kelli Hickle. A new vision for preventing pressure ulcers: wearable wireless devices could help solve
a common-and serious-problem. IEEE pulse, 9(6):28–31, 2014.
[41] Fotios Spyridonis and Gheorghita Ghinea. 3-d pain drawings and seating pressure maps: Relationships and challenges. IEEE Transactions on Information Technology in
Biomedicine, 15(3):409–415, 2011. 3
[42] Yating Tian, Hongwen Zhang, Yebin Liu, and Limin Wang. Recovering 3d human mesh from monocular images: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023. 3
[43] Alexander Toshev and Christian Szegedy. Deeppose: Human pose estimation via deep neural networks. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 1653–1660, 2014. 3
[44] Gurjot S Walia, Alison L Wong, Andrea Y Lo, Gina A Mackert, Hannah M Carl, Rachel A Pedreira, Ricardo Bello, Carla S Aquino, William V Padula, and Justin M Sacks. Efficacy of monitoring devices in support of prevention of pressure injuries: systematic review and meta-analysis. Advances in skin & wound care, 29(12):567–574, 2016. 1
[45] Keze Wang, Liang Lin, Chenhan Jiang, Chen Qian, and Pengxu Wei. 3d human pose machines with self-supervised learning. IEEE transactions on pattern analysis and machine
intelligence, 42(5):1069–1082, 2019. 3