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A Survey on Human Pose Estimation


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Abstract

Human pose estimation has attracted widespread attention due to its important application value and theoretical significance. A systemic survey of human pose estimation would be very meaningful. However, relevant studies have significantly lagged behind in this respect. To this end, we discuss the difficulties of human pose estimation and give a data-driven overview of recent approaches to performing human pose estimation, including depth-based approaches and traditional image-based methods. While the focus of this study is on approaches using depth and RGB image data, we also discuss human pose estimation methods based on object detection and action recognition. Finally, we give some analysis advice to researchers.


Keywords


Pages

Total Pages: 7
Pages: 483-489

DOI
10.1080/10798587.2015.1095419


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Published

Volume: 22
Issue: 3
Year: 2015

Cite this document


References

Aggarwal J. K. Motion analysis: Past, present and future

Aggarwal, J.K., and M.S. Ryoo. "Human Activity Analysis." ACM Computing Surveys 43.3 (2011): 1-43. Crossref. Web. https://doi.org/10.1145/1922649.1922653

Bourdev L. Proceedings

Felzenszwalb, P F et al. "Object Detection with Discriminatively Trained Part-Based Models." IEEE Transactions on Pattern Analysis and Machine Intelligence 32.9 (2010): 1627-1645. Crossref. Web. https://doi.org/10.1109/TPAMI.2009.167

Felzenszwalb, Pedro F., and Daniel P. Huttenlocher. "Pictorial Structures for Object Recognition." International Journal of Computer Vision 61.1 (2005): 55-79. Crossref. Web. https://doi.org/10.1023/B:VISI.0000042934.15159.49

Fischler, M.A., and R.A. Elschlager. "The Representation and Matching of Pictorial Structures." IEEE Transactions on Computers C-22.1 (1973): 67-92. Crossref. Web. https://doi.org/10.1109/T-C.1973.223602

Gupta, A., A. Kembhavi, and L.S. Davis. "Observing Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition." IEEE Transactions on Pattern Analysis and Machine Intelligence 31.10 (2009): 1775-1789. Crossref. Web. https://doi.org/10.1109/TPAMI.2009.83

Johnson, Sam, and Mark Everingham. "Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation." Procedings of the British Machine Vision Conference 2010 (2010): n. pag. Crossref. Web. https://doi.org/10.5244/C.24.12

Klette R. Understanding human motion: A historic review

Shotton, Jamie et al. "Efficient Human Pose Estimation from Single Depth Images." IEEE Transactions on Pattern Analysis and Machine Intelligence 35.12 (2013): 2821-2840. Crossref. Web. https://doi.org/10.1109/TPAMI.2012.241

Shotton, Jamie et al. "Real-Time Human Pose Recognition in Parts from Single Depth Images." Communications of the ACM 56.1 (2013): 116. Crossref. Web. https://doi.org/10.1145/2398356.2398381

Yang, Xiaodong, and YingLi Tian. "Effective 3D Action Recognition Using EigenJoints." Journal of Visual Communication and Image Representation 25.1 (2014): 2-11. Crossref. Web. https://doi.org/10.1016/j.jvcir.2013.03.001

Yang, Yi, and Deva Ramanan. "Articulated Human Detection with Flexible Mixtures of Parts." IEEE Transactions on Pattern Analysis and Machine Intelligence 35.12 (2013): 2878-2890. Crossref. Web. https://doi.org/10.1109/TPAMI.2012.261

Bangpeng Yao, and Li Fei-Fei. "Recognizing Human-Object Interactions in Still Images by Modeling the Mutual Context of Objects and Human Poses." IEEE Transactions on Pattern Analysis and Machine Intelligence 34.9 (2012): 1691-1703. Crossref. Web. https://doi.org/10.1109/TPAMI.2012.67

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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