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PoseAnalyser: A Survey on Human Pose Estimation

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Abstract

Human pose estimation is the process of detecting the body keypoints of a person and can be used to classify different poses. Many researchers have proposed various ways to get a perfect 2D as well as a 3D human pose estimator that could be applied for various types of applications. This paper is a review of all the state-of-the-art architectures based on human pose estimation, the papers referred were based on the types of computer vision and machine learning algorithms, such as feed-forward neural networks, convolutional neural networks (CNN), OpenPose, MediaPipe, and many more. These different approaches are compared on various parameters, like the type of dataset used, the evaluation metric, etc. Different human pose datasets, such as COCO and MPII activity datasets with keypoints, as well as specific application-based datasets, are reviewed in this survey paper. Researchers may use these architectures and datasets in a range of domains, which are also discussed. The paper analyzes several approaches and architectures that can be used as a guide for other researchers to assist them in developing better techniques to achieve high accuracy.

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Data Availability

The datasets analysed during the current study are included in this published article. For eg. Section "Dataset" and Table 2 consist of relevant information.

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Acknowledgements

This research was supported by IFM Engineering Private Limited, in association with the Department of Electronics and Telecommunication at Vishwakarma Institute of Technology, Pune. A special thanks to Prof. Vaishali Jabade for her constant support and Mr. Aniket Patil, from the IFM team, for guiding us throughout the research.

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Authors and Affiliations

  1. Vishwakarma Institute of Technology, Pune, India

    Sakshi Kulkarni, Shubham Deshmukh, Favin Fernandes & Vaishali Jabade

  2. Ifm Engineering Private Limited, Pune, India

    Aniket Patil

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  1. Sakshi Kulkarni
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  2. Shubham Deshmukh
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  3. Favin Fernandes
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  4. Aniket Patil
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  5. Vaishali Jabade
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Correspondence to Sakshi Kulkarni.

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Kulkarni, S., Deshmukh, S., Fernandes, F. et al. PoseAnalyser: A Survey on Human Pose Estimation. SN COMPUT. SCI. 4, 136 (2023). https://doi.org/10.1007/s42979-022-01567-2

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