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International Journal of Multimedia Information Retrieval
Erschienen in: International Journal of Multimedia Information Retrieval 4/2022

19.11.2022 | Trends and Surveys

Human pose estimation using deep learning: review, methodologies, progress and future research directions

verfasst von: Pranjal Kumar, Siddhartha Chauhan, Lalit Kumar Awasthi

Erschienen in: International Journal of Multimedia Information Retrieval | Ausgabe 4/2022

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Abstract

Human pose estimation (HPE) has developed over the past decade into a vibrant field for research with a variety of real-world applications like 3D reconstruction, virtual testing and re-identification of the person. Information about human poses is also a critical component in many downstream tasks, such as activity recognition and movement tracking. This review focuses on the key aspects of deep learning in the development of both 2D & 3D HPE. It provides detailed information on the variety of databases, performance metrics and human body models incorporated for implementing HPE methodologies. This paper discusses variety of applications of HPE across domains like activity recognition, animation and gaming, virtual reality, video tracking, etc. The paper presents an analytical study of all the major works that use deep learning methods for various downstream tasks in each domain for both 2D & 3D HPE. Finally, it discusses issues and limitations in the current topic of HPE and recommend potential future research directions in order to make meaningful progress in this area.
Vorheriger Artikel Contrastive self-supervised learning: review, progress, challenges and future research directions
Nächster Artikel Special issue on cross-modal retrieval and analysis

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Metadaten
Titel
Human pose estimation using deep learning: review, methodologies, progress and future research directions
verfasst von
Pranjal Kumar
Siddhartha Chauhan
Lalit Kumar Awasthi
Publikationsdatum
19.11.2022
Verlag
Springer London
Erschienen in
International Journal of Multimedia Information Retrieval / Ausgabe 4/2022
Print ISSN: 2192-6611
Elektronische ISSN: 2192-662X
DOI
https://doi.org/10.1007/s13735-022-00261-6

Weitere Artikel der Ausgabe 4/2022

International Journal of Multimedia Information Retrieval 4/2022 Zur Ausgabe

Editorial

Special issue on cross-modal retrieval and analysis

Regular Paper

Video deblurring and flow-guided feature aggregation for obstacle detection in agricultural videos

Regular Paper

Semantic-aware visual scene representation

Regular Paper

Prototype local–global alignment network for image–text retrieval

Regular Paper

Multimodal Quasi-AutoRegression: forecasting the visual popularity of new fashion products

Regular Paper

Similar interior coordination image retrieval with multi-view features

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