skip to main content
research-article

Recognizing 3D Trajectories as 2D Multi-stroke Gestures

Authors Info & Claims
Published:04 November 2020Publication History
Skip Abstract Section

Abstract

While end users can acquire full 3D gestures with many input devices, they often capture only 3D trajectories, which are 3D uni-path, uni-stroke single-point gestures performed in thin air. Such trajectories with their $(x,y,z)$ coordinates could be interpreted as three 2D stroke gestures projected on three planes,\ie, $XY$, $YZ$, and $ZX$, thus making them admissible for established 2D stroke gesture recognizers. To investigate whether 3D trajectories could be effectively and efficiently recognized, four 2D stroke gesture recognizers, \ie, \$P, \$P+, \$Q, and Rubine, are extended to the third dimension: $\$P^3$, $\$P+^3$, $\$Q^3$, and Rubine-Sheng, an extension of Rubine for 3D with more features. Two new variations are also introduced: $\F for flexible cloud matching and FreeHandUni for uni-path recognition. Rubine3D, another extension of Rubine for 3D which projects the 3D gesture on three orthogonal planes, is also included. These seven recognizers are compared against three challenging datasets containing 3D trajectories, \ie, SHREC2019 and 3DTCGS, in a user-independent scenario, and 3DMadLabSD with its four domains, in both user-dependent and user-independent scenarios, with varying number of templates and sampling. Individual recognition rates and execution times per dataset and aggregated ones on all datasets show a highly significant difference of $\$P+^3$ over its competitors. The potential effects of the dataset, the number of templates, and the sampling are also studied.

Skip Supplemental Material Section

Supplemental Material

References

  1. Roland Aigner, Daniel Wigdor, Hrvoje Benko, Michael Haller, David Lindbauer, Alexandra Ion, Shengdong Zhao, and Jeffrey Tzu Kwan Valino Koh. 2012. Understanding Mid-Air Hand Gestures: A Study of Human Preferences in Usage of Gesture Types for HCI . Technical Report MSR-TR-2012--111. https://www.microsoft.com/en-us/research/publication/understanding-mid-air-hand-gestures-a-study-of-human-preferences-in-usage-of-gesture-types-for-hci/Google ScholarGoogle Scholar
  2. Ahmad Akl and Shahrokh Valaee. 2010. Accelerometer-based gesture recognition via dynamic-time warping, affinity propagation, & compressive sensing. In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. 2270 -- 2273. https://doi.org/10.1109/ICASSP.2010.5495895Google ScholarGoogle ScholarCross RefCross Ref
  3. Lisa Anthony and Jacob O. Wobbrock. 2010. A Lightweight Multistroke Recognizer for User Interface Prototypes. In Proceedings of Graphics Interface 2010 (Ottawa, Ontario, Canada) (GI '10). Canadian Information Processing Society, Toronto, Ont., Canada, Canada, 245--252. http://dl.acm.org/citation.cfm?id=1839214.1839258Google ScholarGoogle Scholar
  4. Lisa Anthony and Jacob O. Wobbrock. 2012. $N-ProTractor: A Fast and Accurate Multistroke Recognizer. In Proceedings of Graphics Interface 2012 (Toronto, Ontario, Canada) (GI '12). Canadian Information Processing Society, Toronto, Ont., Canada, Canada, 117--120. http://dl.acm.org/citation.cfm?id=2305276.2305296Google ScholarGoogle Scholar
  5. F. Argelaguet, M. Ducoffe, A. Lécuyer, and R. Gribonval. 2017. Spatial and rotation invariant 3D gesture recognition based on sparse representation. In 2017 IEEE Symposium on 3D User Interfaces (3DUI) . 158--167.Google ScholarGoogle Scholar
  6. Said Yacine Boulahia, Eric Anquetil, Richard Kulpa, and Franck Multon. 2017. 3D Multistroke Mapping (3DMM): Transfer of Hand-Drawn Pattern Representation for Skeleton-Based Gesture Recognition. In Proceedings of the 12th IEEE International Conference on Automatic Face Gesture Recognition (Washington, DC, USA) (FG '17). IEEE, 462--467. https://doi.org/10.1109/FG.2017.63Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. R. Brunelli. 2009. Template Matching Techniques in Computer Vision: Theory and Practice .John Wiley & Sons, New York.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. F. M. Caputo, S. Burato, G. Pavan, T. Voillemin, H. Wannous, J. P. Vandeborre, M. Maghoumi, E. M. Taranta II, A. Razmjoo, J. J. LaViola Jr., F. Manganaro, S. Pini, G. Borghi, R. Vezzani, R. Cucchiara, H. Nguyen, M. T. Tran, and A. Giachetti. 2019. Online Gesture Recognition. In Eurographics Workshop on 3D Object Retrieval , , Silvia Biasotti, Guillaume Lavoué, and Remco Veltkamp (Eds.). The Eurographics Association. https://doi.org/10.2312/3dor.20191067Google ScholarGoogle Scholar
  9. Fabio Marco Caputo, Pietro Prebianca, Alessandro Carcangiu, Lucio D. Spano, and Andrea Giachetti. 2017. A 3 Cent Recognizer: Simple and Effective Retrieval and Classification of Mid-air Gestures from Single 3D Traces. In Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference, Andrea Giachetti, Paolo Pingi, and Filippo Stanco (Eds.). The Eurographics Association. https://doi.org/10.2312/stag.20171221Google ScholarGoogle Scholar
  10. Fabio M. Caputo, Pietro Prebianca, Alessandro Carcangiu, Lucio D. Spano, and Andrea Giachetti. 2018. Comparing 3D trajectories for simple mid-air gesture recognition. Computers & Graphics , Vol. 73 (2018), 17 -- 25. https://doi.org/10.1016/j.cag.2018.02.009Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Hong Cheng, Lu Yang, and Zicheng Liu. 2016. Survey on 3D Hand Gesture Recognition. IEEE Transactions on Circuits and Systems for Video Technology , Vol. 26, 9 (2016), 1659--1673. https://doi.org/10.1109/TCSVT.2015.2469551Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Adrien Coyette, Sascha Schimke, Jean Vanderdonckt, and Claus Vielhauer. 2007. Trainable Sketch Recognizer for Graphical User Interface Design. In Human-Computer Interaction -- INTERACT 2007, Cécilia Baranauskas, Philippe Palanque, Julio Abascal, and Simone Diniz Junqueira Barbosa (Eds.). Springer, Berlin, Heidelberg, 124--135.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Elena-Gina Craciun, Ionela Rusu, and Radu-Daniel Vatavu. 2016. Free-Hand Gesture Recognizer Pseudocode . http://www.eed.usv.ro/mintviz/projects/GIVISIMP/data/Pseudocode2.pdfGoogle ScholarGoogle Scholar
  14. Richard O. Duda, Peter E. Hart, and David G. Stork. 2000. Pattern Classification .Wiley & Sons, New York.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Bogdan-Florin Gheran, Jean Vanderdonckt, and Radu-Daniel Vatavu. 2018. Gestures for Smart Rings: Empirical Results, Insights, and Design Implications. In Proceedings of the 2018 Designing Interactive Systems Conference (Hong Kong, China) (DIS '18). Association for Computing Machinery, New York, NY, USA, 623--635. https://doi.org/10.1145/3196709.3196741Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. James Herold and Thomas F. Stahovich. 2012. The One Cent Recognizer: A Fast, Accurate, and Easy-to-Implement Handwritten Gesture Recognition Technique. In Eurographics Workshop on Sketch-Based Interfaces and Modeling, Karan Singh and Levent Burak Kara (Eds.). The Eurographics Association. https://doi.org/10.2312/SBM/SBM12/039-046Google ScholarGoogle Scholar
  17. M. Hoffman, P. Varcholik, and J. J. LaViola. 2010. Breaking the status quo: Improving 3D gesture recognition with spatially convenient input devices. In 2010 IEEE Virtual Reality Conference (VR) . 59--66.Google ScholarGoogle Scholar
  18. Jinmiao Huang, Prakhar Jaiswal, and Rahul Rai. 2019. Gesture-based system for next generation natural and intuitive interfaces. Artificial Intelligence for Engineering Design, Analysis and Manufacturing , Vol. 33, 1 (2019), 54--68. https://doi.org/10.1017/S0890060418000045Google ScholarGoogle ScholarCross RefCross Ref
  19. Sven Kratz and Maribeth Back. 2015. Towards Accurate Automatic Segmentation of IMU-Tracked Motion Gestures. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems (Seoul, Republic of Korea) (CHI EA '15). Association for Computing Machinery, New York, NY, USA, 1337--1342. https://doi.org/10.1145/2702613.2732922Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Sven Kratz and Michael Rohs. 2010. A $3 Gesture Recognizer: Simple Gesture Recognition for Devices Equipped with 3D Acceleration Sensors. In Proceedings of the 15th International Conference on Intelligent User Interfaces (Hong Kong, China) (IUI '10). Association for Computing Machinery, New York, NY, USA, 341--344. https://doi.org/10.1145/1719970.1720026Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Sven Kratz and Michael Rohs. 2011. Protractor3D: A Closed-Form Solution to Rotation-Invariant 3D Gestures. In Proceedings of the 16th International Conference on Intelligent User Interfaces (Palo Alto, CA, USA) (IUI '11). Association for Computing Machinery, New York, NY, USA, 371--374. https://doi.org/10.1145/1943403.1943468Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Per Ola Kristensson and Leif C. Denby. 2011. Continuous Recognition and Visualization of Pen Strokes and Touch-Screen Gestures. In Sketch Based Interfaces and Modeling, Vancouver, BC, Canada, 5--7 August 2011. Proceedings, Tracy Hammond and Andrew Nealen (Eds.). Eurographics Association, 95--102. https://doi.org/10.2312/SBM/SBM11/095--102Google ScholarGoogle Scholar
  23. Per-Ola Kristensson and Shumin Zhai. 2004. SHARK2: A Large Vocabulary Shorthand Writing System for Pen-based Computers. In Proceedings of the 17th Annual ACM Symposium on User Interface Software and Technology (Santa Fe, NM, USA) (UIST '04). ACM, New York, NY, USA, 43--52. https://doi.org/10.1145/1029632.1029640Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Lynn Kysh. 2013. Difference between a systematic review and a literature review . (8 2013). https://doi.org/10.6084/m9.figshare.766364.v1Google ScholarGoogle Scholar
  25. Howard Levene. 1960. Robust tests for equality of variances. In Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling , , Ingram Olkin and Harold Hotelling et al. (Eds.). Stanford University Press, Palo Alto, CA, USA, 278--292.Google ScholarGoogle Scholar
  26. Yang Li. 2010. Protractor: A Fast and Accurate Gesture Recognizer. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Atlanta, Georgia, USA) (CHI '10). ACM, New York, NY, USA, 2169--2172. https://doi.org/10.1145/1753326.1753654Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Jiayang Liu, Lin Zhong, Jehan Wickramasuriya, and Venu Vasudevan. 2009. UWave: Accelerometer-Based Personalized Gesture Recognition and Its Applications. Pervasive Mob. Comput. , Vol. 5, 6 (Dec. 2009), 657--675. https://doi.org/10.1016/j.pmcj.2009.07.007Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Mehran Maghoumi and Joseph J. LaViola. 2019. DeepGRU: Deep Gesture Recognition Utility. In Advances in Visual Computing , , George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Daniela Ushizima, Sek Chai, Shinjiro Sueda, Xin Lin, Aidong Lu, Daniel Thalmann, Chaoli Wang, and Panpan Xu (Eds.). Springer International Publishing, Cham, 16--31.Google ScholarGoogle Scholar
  29. Nathan Magrofuoco, Jorge Luis Pé rez-Medina, Paolo Roselli, Jean Vanderdonckt, and Santiago Villarreal. 2019. Eliciting Contact-Based and Contactless Gestures With Radar-Based Sensors. IEEE Access , Vol. 7 (2019), 176982--176997. https://doi.org/10.1109/ACCESS.2019.2951349Google ScholarGoogle ScholarCross RefCross Ref
  30. Antigoni Mezari and Ilias Maglogiannis. 2017. Gesture Recognition Using Symbolic Aggregate Approximation and Dynamic Time Warping on Motion Data. In Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare (Barcelona, Spain) (PervasiveHealth '17). Association for Computing Machinery, New York, NY, USA, 342--347. https://doi.org/10.1145/3154862.3154927Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Meredith Ringel Morris, Andreea Danielescu, Steven Drucker, Danyel Fisher, Bongshin Lee, m. c. schraefel, and Jacob O. Wobbrock. 2014. Reducing Legacy Bias in Gesture Elicitation Studies. Interactions , Vol. 21, 3 (May 2014), 40--45. https://doi.org/10.1145/2591689Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. J. Nielsen. 1994. Usability Engineering .Elsevier Science. lc93000488 https://books.google.be/books?id=95As2OF67f0CGoogle ScholarGoogle ScholarDigital LibraryDigital Library
  33. F. R. Ortega, A. Galvan, K. Tarre, A. Barreto , N. Rishe, J. Bernal , R. Balcazar, and J. Thomas. 2017. Gesture elicitation for 3D travel via multi-touch and mid-Air systems for procedurally generated pseudo-universe. In 2017 IEEE Symposium on 3D User Interfaces (3DUI) . 144--153.Google ScholarGoogle Scholar
  34. J. Reaver, T. F. Stahovich, and J. Herold. 2011. How to Make a Quick$: Using Hierarchical Clustering to Improve the Efficiency of the Dollar Recognizer. In Proceedings of the Eighth Eurographics Symposium on Sketch-Based Interfaces and Modeling (Vancouver, British Columbia, Canada) (SBIM '11). ACM, New York, NY, USA, 103--108. https://doi.org/10.1145/2021164.2021183Google ScholarGoogle Scholar
  35. Dean Rubine. 1991. Specifying Gestures by Example. In Proceedings of the 18th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '91). ACM, New York, NY, USA, 329--337. https://doi.org/10.1145/122718.122753Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Ugo Braga Sangiorgi, Franccois Beuvens, and Jean Vanderdonckt. 2012. User Interface Design by Collaborative Sketching. In Proceedings of the Designing Interactive Systems Conference (Newcastle Upon Tyne, United Kingdom) (DIS '12). Association for Computing Machinery, New York, NY, USA, 378--387. https://doi.org/10.1145/2317956.2318013Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Ovidiu Andrei Schipor, Radu-Daniel Vatavu, and Jean Vanderdonckt. 2019. Euphoria: A Scalable, event-driven architecture for designing interactions across heterogeneous devices in smart environments. Inf. Softw. Technol. , Vol. 109 (2019), 43--59. https://doi.org/10.1016/j.infsof.2019.01.006Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. V. M. Sethu Janaki, S. Babu, and S. S. Sreekanth. 2013. Real time recognition of 3D gestures in mobile devices. In 2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS). 149--152.Google ScholarGoogle Scholar
  39. Jia Sheng. 2004. A Study of AdaBoost in 3D Gesture Recognition . technical report CSC2515. Department of Computer Science, University of Toronto. http://www.dgp.toronto.edu/ jsheng/doc/CSC2515/Report.pdfGoogle ScholarGoogle Scholar
  40. Beat Signer, U. Kurmann, and Moira C. Norrie. 2007. iGesture: A General Gesture Recognition Framework. In 9th International Conference on Document Analysis and Recognition (ICDAR 2007), 23--26 September, Curitiba, Paraná, Brazil. IEEE Computer Society, 954--958. https://doi.org/10.1109/ICDAR.2007.4377056Google ScholarGoogle Scholar
  41. Steven Simske. 2019. Chapter 4 - Meta-analytic design patterns. In Meta-Analytics , , Steven Simske (Ed.). Morgan Kaufmann, 147 -- 185. https://doi.org/10.1016/B978-0--12--814623--1.00004--6Google ScholarGoogle Scholar
  42. Eugene M. Taranta, II and Joseph J. LaViola, Jr. 2015. Penny Pincher: A Blazing Fast, Highly Accurate $-family Recognizer. In Proceedings of the 41st Graphics Interface Conference (Halifax, Nova Scotia, Canada) (GI '15). Canadian Information Processing Society, Toronto, Ont., Canada, Canada, 195--202. http://dl.acm.org/citation.cfm?id=2788890.2788925Google ScholarGoogle Scholar
  43. Eugene M. Taranta II, Amirreza Samiei, Mehran Maghoumi, Pooya Khaloo, Corey R. Pittman, and Joseph J. LaViola Jr. 2017. Jackknife: A Reliable Recognizer with Few Samples and Many Modalities. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI '17). ACM, New York, NY, USA, 5850--5861. https://doi.org/10.1145/3025453.3026002Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Nicanor Valdez, Ronnie Besas, China Yu, Donna Dumalaon, and Rowel Atienza. 2014. 3D gestures on 2D screens for mobile games. In 2014 IEEE Asia Pacific Conference on Wireless and Mobile. 232--237. https://doi.org/10.1109/APWiMob.2014.6920274Google ScholarGoogle ScholarCross RefCross Ref
  45. Jean Vanderdonckt, Nathan Magrofuoco, Suzanne Kieffer, Jorge Pérez, Ysabelle Rase, Paolo Roselli, and Santiago Villarreal. 2019. Head and Shoulders Gestures: Exploring User-Defined Gestures with Upper Body. In Design, User Experience, and Usability. User Experience in Advanced Technological Environments, Aaron Marcus and Wentao Wang (Eds.). Springer International Publishing, Cham, 192--213.Google ScholarGoogle Scholar
  46. Jean Vanderdonckt, Paolo Roselli, and Jorge Luis Pérez-Medina. 2018. !!FTL, an Articulation-Invariant Stroke Gesture Recognizer with Controllable Position, Scale, and Rotation Invariances. In Proceedings of the 20th ACM International Conference on Multimodal Interaction (Boulder, CO, USA) (ICMI '18). Association for Computing Machinery, New York, NY, USA, 125--134. https://doi.org/10.1145/3242969.3243032Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Radu-Daniel Vatavu. 2012. 1F: One Accessory Feature Design for Gesture Recognizers. In Proceedings of the 2012 ACM International Conference on Intelligent User Interfaces (Lisbon, Portugal) (IUI '12). ACM, New York, NY, USA, 297--300. https://doi.org/10.1145/2166966.2167022Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Radu-Daniel Vatavu. 2013. The impact of motion dimensionality and bit cardinality on the design of 3D gesture recognizers. International Journal of Human-Computer Studies , Vol. 71, 4 (2013), 387 -- 409. https://doi.org/10.1016/j.ijhcs.2012.11.005Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Radu-Daniel Vatavu. 2017. Improving Gesture Recognition Accuracy on Touch Screens for Users with Low Vision. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI '17). ACM, New York, NY, USA, 4667--4679. https://doi.org/10.1145/3025453.3025941Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Radu-Daniel Vatavu, Lisa Anthony, and Jacob O. Wobbrock. 2012. Gestures As Point Clouds: A $P Recognizer for User Interface Prototypes. In Proceedings of the 14th ACM International Conference on Multimodal Interaction (Santa Monica, California, USA) (ICMI '12). ACM, New York, NY, USA, 273--280. https://doi.org/10.1145/2388676.2388732Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. Radu-Daniel Vatavu, Lisa Anthony, and Jacob O. Wobbrock. 2014. Gesture Heatmaps: Understanding Gesture Performance with Colorful Visualizations. In Proceedings of the 16th International Conference on Multimodal Interaction (Istanbul, Turkey) (ICMI '14). Association for Computing Machinery, New York, NY, USA, 172--179. https://doi.org/10.1145/2663204.2663256Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. Radu-Daniel Vatavu, Lisa Anthony, and Jacob O. Wobbrock. 2018. $Q: A Super-quick, Articulation-invariant Stroke-gesture Recognizer for Low-resource Devices. In Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services (Barcelona, Spain) (MobileHCI '18). ACM, New York, NY, USA, Article 23, bibinfonumpages12 pages. https://doi.org/10.1145/3229434.3229465Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. Santiago Villarreal-Narvaez, Jean Vanderdonckt, Radu-Daniel Vatavu, and Jacob O. Wobbrock. 2020. A Systematic Review of Gesture Elicitation Studies: What Can We Learn from 216 Studies?. In Proceedings of the 2020 ACM Designing Interactive Systems Conference (Eindhoven, Netherlands) (DIS '20). Association for Computing Machinery, New York, NY, USA, 855--872. https://doi.org/10.1145/3357236.3395511Google ScholarGoogle Scholar
  54. Tracy Westeyn, Helene Brashear, Amin Atrash, and Thad Starner. 2003. Georgia Tech Gesture Toolkit: Supporting Experiments in Gesture Recognition. In Proceedings of the 5th International Conference on Multimodal Interfaces (Vancouver, British Columbia, Canada) (ICMI '03). Association for Computing Machinery, New York, NY, USA, 85--92. https://doi.org/10.1145/958432.958452Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. Jacob O. Wobbrock, Andrew D. Wilson, and Yang Li. 2007. Gestures Without Libraries, Toolkits or Training: A $1 Recognizer for User Interface Prototypes. In Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology (Newport, Rhode Island, USA) (UIST '07). ACM, New York, NY, USA, 159--168. https://doi.org/10.1145/1294211.1294238Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Mais Yasen and Shaidah Jusoh. 2019. A systematic review on hand gesture recognition techniques, challenges and applications. PeerJ Computer Science , Vol. 5 (Sept. 2019), e218. https://doi.org/10.7717/peerj-cs.218Google ScholarGoogle Scholar
  57. Shumin Zhai, Per Ola Kristensson, Caroline Appert, Tue Haste Anderson, and Xiang Cao. 2012. Foundational Issues in Touch-Surface Stroke Gesture Design ? An Integrative Review. Foundations and Trends in Human--Computer Interaction , Vol. 5, 2 (2012), 97--205. https://doi.org/10.1561/1100000012Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Recognizing 3D Trajectories as 2D Multi-stroke Gestures

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader
      About Cookies On This Site

      We use cookies to ensure that we give you the best experience on our website.

      Learn more

      Got it!