Due to a production error, several words were incorrectly capitalized throughout the text. These have now been correctly capitalized.
In Equations 17–20, there were several instances where the authors mistakenly switched the positive and negative signs.
In the Statistical Significance and Simulation of the Models section, subsection Recognition Accuracy and Comparison and End-to-End Deep Learning Architectures, paragraph 12, the authors accidently missed the addition of a footnote. The following footnote has been added for UCF-101: https://www.crcv.ucf.edu/data/UCF101.php.
In Table 7, “Kingma and Ba (2014)” should be replaced with “Tran et al. (2015).” Following that, “Tran et al. (2015)” should be replaced with “Competé et al. (2019).”
In the legend for Figure 6, a sentence has been added to clarify that this is based on “G2,4” where 2 & 4 are pointers.
In the Statistical Significance and Simulation of the Models section, subsection Forecasting Ability for Motion Trajectories, paragraph 2, The final two mentions of “G2,1” have been corrected to “G2,4.”
The publisher and authors apologize for these errors. The original version of this article has been updated.
Summary
Keywords
state-space representation, differential equations, movement modeling, hidden Markov models, gesture recognition, forecasting, motion trajectory
Citation
Frontiers Production Office (2020) Erratum: Human Movement Representation on Multivariate Time Series for Recognition of Professional Gestures and Forecasting Their Trajectories. Front. Robot. AI 7:639181. doi: 10.3389/frobt.2020.639181
Received
08 December 2020
Accepted
08 December 2020
Published
16 December 2020
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
7 - 2020
Updates
Copyright
© 2020 Frontiers Production Office.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Frontiers Production Office, production.office@frontiersin.org
This article was submitted to Sensor Fusion and Machine Perception, a section of the journal Frontiers in Robotics and AI.
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.