Abstract
Object tracking in computer vision can be done either by using a marker-less or marker-based approach. Computer vision systems have been using Fiducial markers for pose estimation in different applications such as augmented reality [5] and robot navigation [4]. With the advancements in Augmented Reality (AR), new tools such as AugmentedReality uco (ArUco) [6] markers have been introduced to the literature. ArUco markers, are used to tackle the localization problem in AR, allowing camera pose estimation to be carried out by a binary matrix. Using a binary matrix not just simplifies the process but also increases the efficiency. As a part of our initiative to create a cost-efficient, 24/7 accessible, Virtual Reality (VR) based chemistry lab for underprivileged students, we wanted to create an alternative way of interacting with the virtual scene. In this study, we used ArUco markers to create a low-cost keyboard only using a piece of paper and an off-the-shelf webcam. We believe this method of keyboard will be more beneficial to the user as they can see the keys before they are typing in the corner of the screen instead of an insufficient on the screen VR keyboard or a regular keyboard where the user can’t see what they are typing with a VR headset. As potential extensions of the base system, we have also designed and evaluated a stereo camera and an IMU sensor based system with various sensor fusion techniques. In summary, the stereo camera reduces occlusion related problems, and the IMU sensor detects vibrations which in turn simplifies the KeyPress detection problem. It has been observed that use of any of these additional sensors improves the overall system performance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
ArUco keyboard demo video: Base system. https://youtu.be/tnKc6zvXliY
ArUco keyboard demo video: IMU sensor based version. https://youtu.be/sIuhZQpu0AE
ArUco keyboard demo video: Stereo camera version (USB3 ZED camera). https://youtu.be/ssbv2NqfAJg
Bacik, J., Durovsky, F., Fedor, P., Perdukova, D.: Autonomous flying with quadrocopter using fuzzy control and ArUco markers. Intell. Serv. Robot. 10(3), 185–194 (2017). https://doi.org/10.1007/s11370-017-0219-8
Billinghurst, M., Clark, A., Lee, G.: A survey of augmented reality. Found. Trends Hum.-Comput. Interact. 8(2–3), 73–272 (2015). http://dx.doi.org/10.1561/1100000049
Garrido-Jurado, S., Muñoz-Salinas, R., Madrid-Cuevas, F., MarĂn-JimĂ©nez, M.: Automatic generation and detection of highly reliable fiducial markers under occlusion. Pattern Recogn. 47(6), 2280–2292 (2014). https://doi.org/10.1016/j.patcog.2014.01.005
Acknowledgments
Funding is provided by NSF-1919855, Advanced Mobility Institute grants GR-2000028, GR-2000029, and Florida Polytechnic University startup grant GR-1900022.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendices
Appendix I: ArUco Code Detection Module aruco_tools.py
Appendix II: Base System minikdb_mono.py
Appendix III: IMU Based System minikbd_imu.py
Appendix IV: Stereo Camera Based System minikbd_zed.py
Appendix V: IMU Sensor Code for Arduino Uno
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Toker, O., Karaman, B., Demirel, D. (2022). A Paper-Based Keyboard Using ArUco Codes: ArUco Keyboard. In: Kurosu, M. (eds) Human-Computer Interaction. Technological Innovation. HCII 2022. Lecture Notes in Computer Science, vol 13303. Springer, Cham. https://doi.org/10.1007/978-3-031-05409-9_15
Download citation
DOI: https://doi.org/10.1007/978-3-031-05409-9_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-05408-2
Online ISBN: 978-3-031-05409-9
eBook Packages: Computer ScienceComputer Science (R0)