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[해외논문] Development of Real-Time Hand Gesture Recognition for Tabletop Holographic Display Interaction Using Azure Kinect 원문보기

Sensors, v.20 no.16, 2020년, pp.4566 -   

Lee, Chanhwi (Department of Electronic Engineering, Kwangwoon University, Seoul 01897, Korea) ,  Kim, Jaehan (chanheui0102@gmail.com (C.L.)) ,  Cho, Seoungbae (jsyoo@kw.ac.kr (J.Y.)) ,  Kim, Jinwoong (Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea) ,  Yoo, Jisang (kimjhan@etri.re.kr (J.K.)) ,  Kwon, Soonchul (csb60237@etri.re.kr (S.C.))

Abstract AI-Helper 아이콘AI-Helper

The use of human gesturing to interact with devices such as computers or smartphones has presented several problems. This form of interaction relies on gesture interaction technology such as Leap Motion from Leap Motion, Inc, which enables humans to use hand gestures to interact with a computer. The...

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참고문헌 (30)

  1. 1. Ren Z. Yuan J. Meng J. Zhang Z. Robust part-based hand gesture recognition using kinect sensor IEEE Trans. Multimed. 2013 15 1110 1120 10.1109/TMM.2013.2246148 

  2. 2. Biswas K.K. Basu S.K. Gesture recognition using microsoft kinect In Proceeding of the 5th International Conference on Automation, Robotics and Applications, James Cook Hotel Wellington, New Zealand 6?8 December 2011 100 103 

  3. 3. Li Y. Hand gesture recognition using Kinect In Proceeding of the 2012 IEEE International Conference on Computer Science and Automation Engineering Zhangjiajie, China 25?27 May 2012 196 199 

  4. 4. Marin G. Dominio F. Zanuttigh P. Hand gesture recognition with leap motion and kinect devices In Proceeding of the 2014 IEEE International Conference on Image Processing La Defense, Paris, France 27?30 October 2014 1565 1569 

  5. 5. Patsadu O. Nukoolkit C. Watanapa B. Human gesture recognition using Kinect camera In Proceeding of the 2012 Ninth International Conference on Computer Science and Software Engineering Bangkok, Thailand 30 May?1 June 2012 28 32 

  6. 6. Guzsvinecz T. Szucs V. Sik-Lanyi C. Suitability of the Kinect sensor and Leap Motion controller―A literature review Sensors 2019 19 1072 10.3390/s19051072 30832385 

  7. 7. He G.F. Kang S.K. Song W.C. Jung S.T. Real-time gesture recognition using 3D depth camera In Proceeding of the 2011 IEEE 2nd International Conference on Software Engineering and Service Science Beijing, China 15 July 2011 187 190 

  8. 8. Ito A. Nakada K. UI Design based on Traditional Japanese Gesture In Proceeding of the 2019 10th IEEE International Conference on Cognitive Infocommunications Naples, Italy 23?25 October 2019 85 90 

  9. 9. Ferri J. Llinares Llopis R. Moreno J. Ibanez Civera J. Garcia-Breijo E. A wearable textile 3D gesture recognition sensor based on screen-printing technology Sensors 2019 19 5068 10.3390/s19235068 31757058 

  10. 10. Zsolczay R. Brown R. Maire F. Turkay S. Vague gesture control: Implications for burns patients In Proceeding of the 31st Australian Conference on Human-Computer-Interaction Fremantle, Australia 3?5 December 2019 524 528 

  11. 11. Jiang L. Xia M. Liu X. Bai F. Givs: Fine-Grained Gesture Control for Mobile Devices in Driving Environments IEEE Access 2020 8 49229 49243 10.1109/ACCESS.2020.2971849 

  12. 12. Streeter L. Gauch J. Detecting Gestures Through a Gesture-Based Interface to Teach Introductory Programming Concepts In Proceeding of the International Conference on Human-Computer Interaction Vienna, Austria 29?30 July 2020 137 153 

  13. 13. Bakken J.P. Varidireddy N. Uskov V.L. Smart Universities: Gesture Recognition Systems for College Students with Disabilities In Proceeding of the 7th International KES Conference on Smart Education and e-Learning Split, Croatia 17?19 June 2020 393 411 

  14. 14. Kim J. Lim Y. Hong K. Kim H. Kim H.E. Nam J. Park J. Hahn J. Kim Y.J. Electronic tabletop holographic display: Design, implementation, and evaluation Appl. Sci. 2019 9 705 10.3390/app9040705 

  15. 15. Lim Y. Hong K. Kim H.E. Chang E.Y. Lee S. Kim T. Nam J. Choo H.G. Kim J. Hahn J. 360-degree tabletop electronic holographic display Opt. Express 2016 24 24999 25009 10.1364/OE.24.024999 27828440 

  16. 16. Chang E.Y. Choi J. Lee S. Kwon S. Yoo J. Park M. Kim J. 360-degree color hologram generation for real 3D objects Appl. Opt. 2018 57 A91 A100 10.1364/AO.57.000A91 29328134 

  17. 17. Nguyen X.S. Brun L. Lezoray O. Bougleux S. A neural network based on SPD manifold learning for skeleton-based hand gesture recognition Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Long Beach, CA, USA 16?20 June 2019 12036 12045 

  18. 18. Wan C. Probst T. Gool L.V. Yao A. Self-supervised 3d hand pose estimation through training by fitting Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Long Beach, CA, USA 16?20 June 2019 10853 10862 

  19. 19. Du K. Lin X. Sun Y. Ma X. Crossinfonet: Multi-task information sharing based hand pose estimation Proceedings of the 2019 IEEE Conference on Computer Vision and Pattern Recognition Long Beach, CA, USA 16?20 June 2019 9896 9905 

  20. 20. Wang C. Liu Z. Chan S.C. Superpixel-based hand gesture recognition with kinect depth camera IEEE Trans. Multimed. 2014 17 29 39 10.1109/TMM.2014.2374357 

  21. 21. Supancic J.S. Rogez G. Yang Y. Shotton J. Ramanan D. Depth-based hand pose estimation: Data, methods, and challenges Proceedings of the IEEE International Conference on Computer Vision Santiago, Chile 7?13 December 2015 1868 1876 

  22. 22. Joo S.I. Weon S.H. Choi H.I. Real-time depth-based hand detection and tracking Sci. World J. 2014 2014 1 17 10.1155/2014/284827 24737965 

  23. 23. Liu X. Fujimura K. Hand gesture recognition using depth data Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition Seoul, Korea 19 May 2004 529 534 

  24. 24. Poularakis S. Katsavounidis I. Finger detection and hand posture recognition based on depth information Proceedings of the 2014 IEEE International Conference on Acoustics, Speech and Signal Processing Florence, Italy 4?9 May 2014 4329 4333 

  25. 25. Ren Z. Meng J. Yuan J. Depth camera based hand gesture recognition and its applications in human-computer-interaction Proceedings of the 2011 8th International Conference on Information, Communications Signal Processing Singapore 13?16 December 2011 1 5 

  26. 26. Yu M. Kim N. Jung Y. Lee S. A Frame Detection Method for Real-Time Hand Gesture Recognition Systems Using CW-Radar Sensors 2020 20 2321 10.3390/s20082321 32325709 

  27. 27. Abavisani M. Joze H.R.V. Patel V.M. Improving the performance of unimodal dynamic hand-gesture recognition with multimodal training Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Long Beach, CA, USA 16?20 June 2019 1165 1174 

  28. 28. Lee S.H. Lee G.C. Yoo J. Kwon S. Wisenetmd: Motion detection using dynamic background region analysis Symmetry 2019 11 621 10.3390/sym11050621 

  29. 29. Yin Y. Randall D. Gesture spotting and recognition using salience detection and concatenated hidden markov models Proceedings of the 15th ACM on International conference on multimodal interaction, Coogee Bay Hotel Sydney, Australia 9?12 December 2013 489 494 

  30. 30. Kim J.H. Hong G.S. Kim B.G. Dogra D.P. deepGesture: Deep learning-based gesture recognition scheme using motion sensors Displays 2018 55 38 45 10.1016/j.displa.2018.08.001 

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