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2020, 2(6): 534-555

Published Date:2020-12-20 DOI: 10.1016/j.vrih.2020.10.001

Affine transformation of virtual 3D object using 2D localization of fingertips

Abstract

Background
Interactions with virtual 3D objects in the virtual reality (VR) environment using the gesture of fingers captured in a wearable 2D camera have emerging applications in real-life.
Method
This paper presents an approach of a two-stage convolutional neural network, one for the detection of hand and another for the fingertips. One purpose of VR environments is to transform a virtual 3D object with affine parameters by using the gesture of thumb and index fingers.
Results
To evaluate the performance of the proposed system, one existing, and another developed egocentric fingertip databases are employed so that learning involves large variations that are common in real-life. Experimental results show that the proposed fingertip detection system outperforms the existing systems in terms of the precision of detection.
Conclusion
The interaction performance of the proposed system in the VR environment is higher than that of the existing systems in terms of estimation error and correlation between the ground truth and estimated affine parameters.

Keyword

Affine transformation ; Detection of fingertips ; Detection of hand ; Human-computer interaction ; Virtual reality

Cite this article

Mohammad Mahmudul ALAM, S. M. Mahbubur RAHMAN. Affine transformation of virtual 3D object using 2D localization of fingertips. Virtual Reality & Intelligent Hardware, 2020, 2(6): 534-555 DOI:10.1016/j.vrih.2020.10.001

References

1. Burdea G C, Coiffet P. Virtual reality technology. John Wiley & Sons, 2003

2. Azuma R, Baillot Y, Behringer R, Feiner S, Julier S, MacIntyre B. Recent advances in augmented reality. IEEE Computer Graphics and Applications, 2001, 21(6): 34–47 DOI:10.1109/38.963459

3. Milgram P, Kishino F. A taxonomy of mixed reality visual displays. IEICE Transactions on Information and Systems, 1994, 12: 1321–1329

4. Canessa A, Chessa M, Gibaldi A, Sabatini S P, Solari F. Calibrated depth and color cameras for accurate 3D interaction in a stereoscopic augmented reality environment. Journal of Visual Communication and Image Representation, 2014, 25(1): 227–237 DOI:10.1016/j.jvcir.2013.02.011

5. Bernardes J. Comparing a mouse and a free hand gesture interaction technique for 3D object manipulation. In: Lecture Notes in Computer Science. Cham: Springer International Publishing, 2020, 19–37 DOI:10.1007/978-3-030-49062-1_2

6. Feng Z Y, Xu S J, Zhang X, Jin L W, Ye Z C, Yang W X. Real-time fingertip tracking and detection using Kinect depth sensor for a new writing-in-the air system. In: Proceedings of the 4th International Conference on Internet Multimedia Computing and Service-ICIMCS'12. Wuhan, China, NewYork, Press ACM, 2012, 70–74 DOI:10.1145/2382336.2382356

7. Han J G, Shao L, Xu D, Shotton J. Enhanced computer vision with microsoft kinect sensor: a review. IEEE Transactions on Cybernetics, 2013, 43(5): 1318–1334 DOI:10.1109/tcyb.2013.2265378

8. Nai W Z, Liu Y, Rempel D, Wang Y T. Fast hand posture classification using depth features extracted from random line segments. Pattern Recognition, 2017, 65: 1–10 DOI:10.1016/j.patcog.2016.11.022

9. Kang S K, Nam M Y, Rhee P K. Color based hand and finger detection technology for user interaction. In: 2008 International Conference on Convergence and Hybrid Information Technology. Daejeon, South Korea, IEEE, 2008, 229–236

10. Gurav R M, Kadbe P K. Real time finger tracking and contour detection for gesture recognition using OpenCV. 2015

11. Bhuyan M K, MacDorman K F, Kar M K, Neog D R, Lovell B C, Gadde P. Hand pose recognition from monocular images by geometrical and texture analysis. Journal of Visual Languages & Computing, 2015, 28: 39–55 DOI:10.1016/j.jvlc.2014.12.001

12. Stergiopoulou E, Papamarkos N. Hand gesture recognition using a neural network shape fitting technique. Engineering Applications of Artificial Intelligence, 2009, 22(8): 1141–1158 DOI:10.1016/j.engappai.2009.03.008

13. RaySarkar A, Sanyal G, Majumder S. Hand gesture recognition systems: a survey. International Journal of Computer Applications, 2013, 71(15): 25–37 DOI:10.5120/12435-9123

14. Huang Y, Liu X, Jin L, Zhang X. Deepfinger: A cascade convolutional neuron network approach to finger key point detection in egocentric vision with mobile camera. In: 2015 IEEE International Conference on Systems, Man, and Cybernetics. Kowloon, China, IEEE, 2015, 2944–2949

15. Liu X R, Huang Y C, Zhang X, Jin L W. Fingertip in the eye: an attention-based method for real-time hand tracking and fingertip detection in egocentric videos. In: Communications in Computer and Information Science. Singapore: Springer Singapore, 2016, 145–154 DOI:10.1007/978-981-10-3002-4_12

16. Wu W, Li C, Cheng Z, Zhang X, Jin L. Yolse: Egocentric fingertip detection from single RGB images. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV). Venice, Italy, IEEE, 2017, 623–630

17. Jain V, Hebbalaguppe R. AirPen: a touchless fingertip based gestural interface for smartphones and head-mounted devices. 2019

18. Huang Y, Liu X, Zhang X, Jin L. A pointing gesture based egocentric interaction system: Dataset, approach and application. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. Las Vegas, NV, USA, IEEE, 2016, 16–23

19. Poupyrev I, Billinghurst M, Weghorst S, Ichikawa T. The go-go interaction technique: non-linear mapping for direct manipulation in VR. In: Proceedings of the 9th Annual ACM Symposium on User Interface Software and Technology. Seattle, Washington, USA, New York, ACM Press, 1996, 79–80 DOI:10.1145/237091.237102

20. Bowman D A, Hodges L F. An evaluation of techniques for grabbing and manipulating remote objects in immersive virtual environments. In: Proceedings of the symposium on Interactive 3D graphics. Rhode Island, USA, 1997 DOI:10.1145/253284.253301

21. Tomozoe Y, Machida T, Kiyokawa K, Takemura H. Unified gesture-based interaction techniques for object manipulation and navigation in a large-scale virtual environment. In: Proceedings of the IEEE Virtual Reality 2004. Chicago, IL, USA, IEEE, 2004, 259–260

22. Kiyokawa K, Takemura H. A tunnel window and its variations: Seamless teleportation techniques in a virtual environment. In: Proceedings of the HCI International. Citeseer, Las Vegas, Nevada, USA, 2005

23. Lee T, Hollerer T. Handy AR: Markerless inspection of augmented reality objects using fingertip tracking. In: 2007 11th IEEE International Symposium on Wearable Computers. Boston, MA, USA, IEEE, 2007, 83–90 DOI:10.1109/iswc.2007.4373785

24. Rani S S, Dhrisya K, Ahalyadas M. Hand gesture control of virtual object in augmented reality. In: Proceedings of the International Conference Advances in Computing, Communications and Informatics. Udupi, India, IEEE, 2017, 1500–1505

25. Bai H, Gao L, El-Sana J, Billinghurst M. Markerless 3D gesture-based interaction for handheld augmented reality interfaces. In: 2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). Adelaide, SA, Australia, IEEE, 2013, 1–6

26. Song P, Yu H, Winkler S. Vision-based 3D finger interactions for mixed reality games with physics simulation. In: Proceedings of The 7th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry. Singapore, New York, ACM Press, 2008, 7 DOI:10.1145/1477862.1477871

27. Ong S K, Wang Z B. Augmented assembly technologies based on 3D bare-hand interaction. CIRP Annals, 2011, 60(1): 1–4 DOI:10.1016/j.cirp.2011.03.001

28. Le H Q, Kim J I. An augmented reality application with hand gestures for learning 3D geometry. In: 2017 IEEE International Conference on Big Data and Smart Computing (BigComp). Jeju, South Korea, IEEE, 2017, 34–41 DOI:10.1109/BIGCOMP.2017.7881712

29. Weichel C, Lau M, Kim D, Villar N, Gellersen H W. MixFab: a mixed-reality environment for personal fabrication. In: Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems. Toronto, Ontario, Canada, New York, ACM Press, 2014, 3855–3864 DOI:10.1145/2556288.2557090

30. Lee J Y, Rhee G W, Seo D W. Hand gesture-based tangible interactions for manipulating virtual objects in a mixed reality environment. The International Journal of Advanced Manufacturing Technology, 2010, 51(9/10/11/12): 1069–1082 DOI:10.1007/s00170-010-2671-x

31. Alam M M, Rahman S M. Detection and tracking of fingertips for geometric transformation of objects in virtual environment. In: 2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA). Abu Dhabi, United Arab Emirates, IEEE, 2019, 1–8 DOI:10.1109/AICCSA47632.2019.9035256

32. Wu M Y, Ting P W, Tang Y H, Chou E T, Fu L C. Hand pose estimation in object-interaction based on deep learning for virtual reality applications. Journal of Visual Communication and Image Representation, 2020, 70: 102802 DOI:10.1016/j.jvcir.2020.102802

33. Redmon J, Farhadi A. YOLO9000: better, faster, stronger. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Honolulu, HI, USA, IEEE, 2017, 7263–7271

34. Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition. 2014

35. Szegedy C, Vanhoucke V, Ioffe S, Shlens J, Wojna Z. Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV, USA, IEEE, 2016, 2818–2826

36. Chollet F. Xception: Deep learning with depthwise separable convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, HI, USA, IEEE, 2017, 1251–1258

37. Sandler M, Howard A, Zhu M, Zhmoginov A, Chen L C. Mobilenetv2: Inverted residuals and linear bottlenecks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Salt Lake City, UT, USA, IEEE, 2018, 4510–4520

38. Kingma D P, Ba J. Adam: a method for stochastic optimization. 2014

39. Anton H, Rorres C. Elementary linear algebra: applications version. John Wiley & Sons, 2013

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