Human Pose Estimation - Methods and Applications: Analyzing methods and applications of human pose estimation for inferring body joint positions from images or videos

Authors

  • Dr. Sébastien Lachapelle Associate Professor of Geomatics Engineering, University of Calgary, Canada Author

Keywords:

Human Pose Estimation, Computer Vision

Abstract

Human pose estimation is a critical task in computer vision with applications in various fields such as healthcare, sports analysis, and human-computer interaction. This paper provides an overview of the methods and applications of human pose estimation, focusing on the inference of body joint positions from images or videos. We analyze the evolution of pose estimation techniques from traditional methods to deep learning-based approaches, highlighting their strengths and limitations. Additionally, we discuss the applications of pose estimation in areas such as action recognition, pose-based human-computer interaction, and sports analytics. This paper aims to provide researchers and practitioners with a comprehensive understanding of human pose estimation methods and their diverse applications.

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References

K. Joel Prabhod, “ASSESSING THE ROLE OF MACHINE LEARNING AND COMPUTER VISION IN IMAGE PROCESSING,” International Journal of Innovative Research in Technology, vol. 8, no. 3, pp. 195–199, Aug. 2021, [Online]. Available: https://ijirt.org/Article?manuscript=152346

Sadhu, Amith Kumar Reddy, and Ashok Kumar Reddy Sadhu. "Fortifying the Frontier: A Critical Examination of Best Practices, Emerging Trends, and Access Management Paradigms in Securing the Expanding Internet of Things (IoT) Network." Journal of Science & Technology 1.1 (2020): 171-195.

Tatineni, Sumanth, and Anjali Rodwal. “Leveraging AI for Seamless Integration of DevOps and MLOps: Techniques for Automated Testing, Continuous Delivery, and Model Governance”. Journal of Machine Learning in Pharmaceutical Research, vol. 2, no. 2, Sept. 2022, pp. 9-41, https://pharmapub.org/index.php/jmlpr/article/view/17.

Pulimamidi, Rahul. "Leveraging IoT Devices for Improved Healthcare Accessibility in Remote Areas: An Exploration of Emerging Trends." Internet of Things and Edge Computing Journal 2.1 (2022): 20-30.

Gudala, Leeladhar, et al. "Leveraging Biometric Authentication and Blockchain Technology for Enhanced Security in Identity and Access Management Systems." Journal of Artificial Intelligence Research 2.2 (2022): 21-50.

Sadhu, Ashok Kumar Reddy, and Amith Kumar Reddy. "Exploiting the Power of Machine Learning for Proactive Anomaly Detection and Threat Mitigation in the Burgeoning Landscape of Internet of Things (IoT) Networks." Distributed Learning and Broad Applications in Scientific Research 4 (2018): 30-58.

Tatineni, Sumanth, and Venkat Raviteja Boppana. "AI-Powered DevOps and MLOps Frameworks: Enhancing Collaboration, Automation, and Scalability in Machine Learning Pipelines." Journal of Artificial Intelligence Research and Applications 1.2 (2021): 58-88.

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Published

09-06-2022

How to Cite

[1]
Dr. Sébastien Lachapelle, “Human Pose Estimation - Methods and Applications: Analyzing methods and applications of human pose estimation for inferring body joint positions from images or videos”, Distrib Learn Broad Appl Sci Res, vol. 8, pp. 100–107, Jun. 2022, Accessed: Nov. 07, 2024. [Online]. Available: https://dlabi.org/index.php/journal/article/view/62

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