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Open AccessArticle

Filling the Joints: Completion and Recovery of Incomplete 3D Human Poses

Institute of Computer Science, FORTH and Computer Science Department, University of Crete, GR-70013 Crete, Greece
Institute of Computer Science, FORTH, GR-70013 Crete, Greece
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in Proceedings of the 11th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA 2018), Island of Corfu, Greece, 26–29 June 2018.
Technologies 2018, 6(4), 97;
Received: 5 October 2018 / Revised: 26 October 2018 / Accepted: 27 October 2018 / Published: 30 October 2018
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
PDF [744 KB, uploaded 5 November 2018]


We present a comparative study of three matrix completion and recovery techniques based on matrix inversion, gradient descent, and Lagrange multipliers, applied to the problem of human pose estimation. 3D human pose estimation algorithms may exhibit noise or may completely fail to provide estimates for some joints. A post-process is often employed to recover the missing joints’ locations from the remaining ones, typically by enforcing kinematic constraints or by using a prior learned from a database of natural poses. Matrix completion and recovery techniques fall into the latter category and operate by filling-in missing entries of a matrix whose available/non-missing entries may be additionally corrupted by noise. We compare the performance of three such techniques in terms of the estimation error of their output as well as their runtime, in a series of simulated and real-world experiments. We conclude by recommending use cases for each of the compared techniques. View Full-Text
Keywords: matrix completion; matrix recovery; human pose estimation; comparative study matrix completion; matrix recovery; human pose estimation; comparative study

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Bautembach, D.; Oikonomidis, I.; Argyros, A. Filling the Joints: Completion and Recovery of Incomplete 3D Human Poses. Technologies 2018, 6, 97.

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