A Non-Contact Height Measurement Method Using Mediapipe and Yolov8 in a Three-Dimension Space

Phu Nguyen Trung; Dat Dong Quoc; Kien Nguyen Phan

doi:10.37385/jaets.v7i2.8798

Authors

Phu Nguyen Trung Hanoi University of Industry
Dat Dong Quoc Hanoi University of Science and Technology
Kien Nguyen Phan Hanoi University of Science and Technology

DOI:

https://doi.org/10.37385/jaets.v7i2.8798

Keywords:

non-contact, mediaPipe, 3D space, height measurement

Abstract

Accurate human height measurement is an essential clinical parameter for calculating body mass index and assessing patient health status. However, traditional contact-based or manual methods are impractical for patients with limited mobility or during emergency conditions. This study addresses this limitation by developing a non-contact 3D height estimation system using a smartphone-based vision approach. The system employs MediaPipe to extract skeletal landmarks and a regression model to predict human height from bone segment lengths and a reference object. Experimental evaluation on 166 subjects across multiple positions demonstrates a high accuracy with an average error rate of 1.54 ± 0.64%, outperforming most existing camera-based systems. The proposed method offers a practical, low-cost, and portable solution for medical height assessment, particularly beneficial in clinical and emergency settings. Potential limitations include dependence on camera angle and lighting conditions, which will be addressed in future work.

Downloads

Download data is not yet available.

References

Ahmad, B., Islam, F., Ansari, M. I., Taimoor, L., Arif, M. S., ur Rehman Memon, A., Umair, M., & Abubaker, J. (2025). Seeing Isn’t measuring: ICU staff’s ability to estimate patient height and weight — A cross-sectional study from Pakistan’s largest cardiac centre. BMJ Open, 15(9), e102507. https://doi.org/10.1136/bmjopen-2025-102507

Anh, V. T., Huy, T. Q., Phan, K. N., Linh, N. N., Tran, D. T., & Minh, N. C. (2024, December). Non-contact Height Measurement in 2D with Horizontal Rotation Pose. In International Conference on Engineering Research and Applications (pp. 450-457). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-03859-3_47

Bradski, G. (2000). The OpenCV Library. Dr. Dobb’s Journal Ftware Tools for the Professional Programmer, 120–123.

Chai, Y., & Cao, X. (2018). A Real-Time Human Height Measurement Algorithm Based on Monocular Vision. 2018 2nd IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC), 293–297. https://doi.org/10.1109/IMCEC.2018.8469428

Chang, H., Li, D., Zhang, X., Cui, X., Fu, Z., Chen, X., & Song, Y. (2024). Real-time height measurement with a line-structured-light based imaging system. Sensors and Actuators A: Physical, 368, 115164. https://doi.org/10.1016/j.sna.2024.115164

Ciampini, C., Petrillo, A., Zomparelli, F., & Groutas, S. (2024). An innovative method for human height estimation combining video images and 3D laser scanning. Journal of Forensic Sciences, 69(1), 301–315. https://doi.org/10.1111/1556-4029.15378

Dennis, D. M., Hunt, E. E., & Budgeon, C. A. (2015). Measuring Height in Recumbent Critical Care Patients. American Journal of Critical Care, 24(1), 41–47. https://doi.org/10.4037/ajcc2015761

Dill, S., Ahmadi, A., Grimmer, M., Haufe, D., Rohr, M., Zhao, Y., Sharbafi, M., & Hoog Antink, C. (2024). Accuracy Evaluation of 3D Pose Reconstruction Algorithms Through Stereo Camera Information Fusion for Physical Exercises with MediaPipe Pose. Sensors, 24(23), 7772. https://doi.org/10.3390/s24237772

Dokthurian, S., Rattanapitak, W., & Wangsiripitak, S. (2021). Human Height Estimation Using Visual Geometry and Feature Learning. 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1–5. https://doi.org/10.1109/ISCAS51556.2021.9401250

Duc, T. T., Phan, K. N., Lan, P. N., Thi Mai, P. B., Ngoc, D. C., Manh, H. N., Hoang, O. Le, & Trung, P. N. (2023). Design and Development of Bedside Scale with Embedded Software to Calculate Treatment Parameters for Resuscitated Patients. 2023 1st International Conference on Health Science and Technology (ICHST), 1–6. https://doi.org/10.1109/ICHST59286.2023.10565330

Efeti, M. S., Shey, N. D., & Vubo, E. Y. (2025). Body Mass Index (BMI) in Association with Diabetes, Hypertension, Comorbidity among Patients in the Buea Health District, Cameroon. Journal of Advances in Medical and Pharmaceutical Sciences, 27(9), 1–16. https://doi.org/10.9734/jamps/2025/v27i9812

Eriks-Hoogland, I., Hilfiker, R., Baumberger, M., Balk, S., Stucki, G., & Perret, C. (2011). Clinical assessment of obesity in persons with spinal cord injury: validity of waist circumference, body mass index, and anthropometric index. The Journal of Spinal Cord Medicine, 34(4), 416–422. https://doi.org/10.1179/2045772311Y.0000000014

Haritosh, A., Gupta, A., Chahal, E. S., Misra, A., & Chandra, S. (2019). A novel method to estimate Height, Weight and Body Mass Index from face images. 2019 Twelfth International Conference on Contemporary Computing (IC3), 1–6. https://doi.org/10.1109/IC3.2019.8844872

Ismail, N. A., Tan, C. W., Mohamed, S. E., Salam, M. S., & Ghaleb, F. A. (2020). Mobile based augmented reality for flexible human height estimation using touch and motion gesture interaction. IOP Conference Series: Materials Science and Engineering, 979(1), 012017. https://doi.org/10.1088/1757-899X/979/1/012017

Kappan, M. M., Sandoval, E. B., Meijering, E., & Cruz, F. (2025). A survey on deep learning for 2D and 3D human pose estimation. Artificial Intelligence Review, 59(1), 32. https://doi.org/10.1007/s10462-025-11430-4

Khanna, D., Peltzer, C., Kahar, P., & Parmar, M. S. (2022). Body Mass Index (BMI): A Screening Tool Analysis. Cureus, 14(2). https://doi.org/10.7759/cureus.22119

Kien, N. P., Dat, D. Q., Tran, D. T., & Solanki, V. K. (2024, May). Non-contact Height Measurement in 2D with the Pose of 45° Side Standing. In International Conference on Data & Information Sciences (pp. 367-375). Singapore: Springer Nature Singapore.. https://doi.org/10.1007/978-981-97-9619-9_30

Kien, N. P., Van Thao, H., Tran, D.-T., & Solanki, V. K. (2025). Height Measurement of Pose Bent Knees by Using Pose Estimation of MediaPipe. In International Conference on Data & Information Sciences (pp. 357-365). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-9619-9_29

Kim, I. S., Kim, H., Lee, S., & Jung, S. K. (2023). HeightNet: Monocular Object Height Estimation. Electronics, 12(2), 350. https://doi.org/10.3390/electronics12020350

Kothari, V. P., & Chakurkar, P. S. (2025). Towards safer environments: A YOLO and MediaPipe-based human fall detection system with alert automation. MethodsX, 15, 103623. https://doi.org/10.1016/j.mex.2025.103623

Krzeszowski, T., Dziadek, B., França, C., Martins, F., Gouveia, É. R., & Przednowek, K. (2023). System for Estimation of Human Anthropometric Parameters Based on Data from Kinect v2 Depth Camera. Sensors, 23(7), 3459. https://doi.org/10.3390/s23073459

Lai, H., Tang, Z., & Zhang, X. (2023). RepEPnP: Weakly Supervised 3D Human Pose Estimation with EPnP Algorithm. 2023 International Joint Conference on Neural Networks (IJCNN), 1–8. https://doi.org/10.1109/IJCNN54540.2023.10191300

Lee, D., Kim, J., Jeong, S. C., & Kwon, S. (2020). Human Height Estimation by Color Deep Learning and Depth 3D Conversion. Applied Sciences, 10(16), 5531. https://doi.org/10.3390/app10165531

L’her, E., Martin-Babau, J., & Lellouche, F. (2016). Accuracy of height estimation and tidal volume setting using anthropometric formulas in an ICU Caucasian population. Annals of Intensive Care, 6(1), 55. https://doi.org/10.1186/s13613-016-0154-4

Li, S., Nguyen, V. H., Ma, M., Jin, C.-B., Do, T. D., & Kim, H. (2015). A simplified nonlinear regression method for human height estimation in video surveillance. EURASIP Journal on Image and Video Processing, 2015(1), 32. https://doi.org/10.1186/s13640-015-0086-1

Lin, Y., Jiao, X., & Zhao, L. (2023). Detection of 3D Human Posture Based on Improved Mediapipe. Journal of Computer and Communications, 11(02), 102–121. https://doi.org/10.4236/jcc.2023.112008

Lugaresi, C., Tang, J., Nash, H., McClanahan, C., Uboweja, E., Hays, M., Zhang, F., Chang, C.-L., Yong, M. G., Lee, J., Chang, W.-T., Hua, W., Georg, M., & Grundmann, M. (2019). MediaPipe: A Framework for Building Perception Pipelines. arXiv preprint arXiv:1906.08172. http://arxiv.org/abs/1906.08172

Mikula, A. L., Hetzel, S. J., Binkley, N., & Anderson, P. A. (2016). Clinical height measurements are unreliable: a call for improvement. Osteoporosis International, 27(10), 3041–3047. https://doi.org/10.1007/s00198-016-3635-2

Nayak S S, Sushil Yadav, & Abhimanyu Pradhan. (2024). Effect of Body Mass Index on Effective Dose in Multi Detector Computed Tomography Abdomen Using Automatic Exposure Control. Ethiopian Journal of Health Sciences, 34(6). https://doi.org/10.4314/ejhs.v34i6.9

Nguyen Trung, P., Nguyen, N. B., Nguyen Phan, K., Pham Van, H., Hoang Van, T., Nguyen, T., & Gandjbakhche, A. (2024). A Non-Contacted Height Measurement Method in Two-Dimensional Space. Sensors, 24(21), 6796. https://doi.org/10.3390/s24216796

Nirmal, V., Kameshwaran, J., Sheela, C. V., & Renuka, M. V. (2015). Height measurement in the critically ill patient: A tall order in the critical care unit. Indian Journal of Critical Care Medicine, 19(11), 665–668. https://doi.org/10.4103/0972-5229.169342

O’Neill, S., Kavanagh, R. G., Carey, B. W., Moore, N., Maher, M., & O’Connor, O. J. (2018). Using body mass index to estimate individualised patient radiation dose in abdominal computed tomography. European Radiology Experimental, 2(1), 38. https://doi.org/10.1186/s41747-018-0070-5

Phan, K. N., Nguyen, D. N. N., Thanh, H. D. T., Thuy, A. N., Tran, D.-T., & Thuan, H. T. (2024). Height Measurement of Recumbent Individuals in 2D Space. 2024 International Conference on Control, Robotics and Informatics (ICCRI), 10–14. https://doi.org/10.1109/ICCRI64298.2024.00008

Phan, K. N., Tran Anh, V., Manh, H. P., Thu, H. N., Thuy, N. T., Thi, H. N., Thuy, A. N., & Trung, P. N. (2023). The Non-Contact Height Measurement Method Using MediaPipe and OpenCV in a 2D Space. 2023 1st International Conference on Health Science and Technology (ICHST), 1–6. https://doi.org/10.1109/ICHST59286.2023.10565351

Terven, J., Córdova-Esparza, D.-M., & Romero-González, J.-A. (2023). A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS. Machine Learning and Knowledge Extraction, 5(4), 1680–1716. https://doi.org/10.3390/make5040083

Tonini, A., Painho, M., & Castelli, M. (2022). Estimation of Human Body Height Using Consumer-Level UAVs. Remote Sensing, 14(23), 6176. https://doi.org/10.3390/rs14236176

Trivedi, A., Jain, M., Gupta, N. K., Hinsche, M., Singh, P., Matiaschek, M., Behrens, T., Militeri, M., Birge, C., Kaushik, S., Mohapatra, A., Chatterjee, R., Dodhia, R., & Ferres, J. L. (2021). Height Estimation of Children under Five Years using Depth Images. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 3886–3889. https://doi.org/10.1109/EMBC46164.2021.9630461

Velesaca, H. O., Vulgarin, J., & Vintimilla, B. X. (2023). Deep Learning-based Human Height Estimation from a Stereo Vision System. 2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS), 1–7. https://doi.org/10.1109/ICPRS58416.2023.10179079

Wang, M., Song, Y., Zhao, X., Wang, Y., & Zhang, M. (2024). Utilizing Anthropometric Measurements and 3D Scanning for Health Assessment in Clinical Practice. Physical Activity and Health, 8(1), 182–196. https://doi.org/10.5334/paah.379

Yin, F., & Zhou, S. (2020). Accurate Estimation of Body Height From a Single Depth Image via a Four-Stage Developing Network. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8264–8273. https://doi.org/10.1109/CVPR42600.2020.00829

Zhang, H., Li, G., Li, F., & Jiang, J. (2025). Body Mass Index and the Risk of Hypertension-Diabetes Comorbidity in Elderly Population: A Prospective Cohort in China. Global Heart, 20(1), 97. https://doi.org/10.5334/gh.1487