Abstract
Defocus based Depth estimation has been widely applied for constructing 3D setup from 2D image(s), reconstructing 3D scenes and image refocusing. Using defocus enables us to infer depth information from a single image using visual clues which can be captured by a monocular camera. In this paper, we propose an application of Depth from Defocus to a novel, portable keyboard design. Our estimation technique is based on the concept that depth of the finger with respect to our camera and its defocus blur value is correlated, and a map can be obtained to detect the finger position accurately. We have utilised the near-focus region for our design, assuming that the closer an object is to our camera, more will be its defocus blur. The proposed keyboard can be integrated with smartphones, tablets and Personal Computers, and only requires printing on plain paper or projection on a flat surface. The detection approach involves tracking the finger’s position as the user types, measuring its defocus value when a key is pressed, and mapping the measured defocus together with a precalibrated relation between the defocus amount and the keyboard pattern. This is utilised to infer the finger’s depth, which, along with the azimuth position of the stroke, identifies the pressed key. Our minimalistic design only requires a monocular camera, and there is no need for any external hardware. This makes the proposed approach a cost-effective and feasible solution for a portable keyboard.
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References
Kölsch, M., Turk, M.: Keyboards without keyboards: a survey of virtual keyboards. In: Workshop on Sensing and Input for Media-Centric Systems, Santa Barbara, CA (2002)
Kim, J.R., Tan, H.Z.: Haptic feedback intensity affects touch typing performance on a flat keyboard. In: Auvray, M., Duriez, C. (eds.) EUROHAPTICS 2014. LNCS, vol. 8618, pp. 369–375. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-44193-0_46
Kanevsky, D., Sabath, M., Zlatsin, A.: Virtual invisible keyboard. US Patent 7,042,442, 9 May 2006
Habib, H.A., Mufti, M.: Real time mono vision gesture based virtual keyboard system. IEEE Trans. Consum. Electron. 52(4), 1261–1266 (2006)
Du, H., Charbon, E.: A virtual keyboard system based on multi-level feature matching. In: 2008 Conference on Human System Interactions, pp. 176–181. IEEE (2008)
Murase, T., Moteki, A., Suzuki, G., Nakai, T., Hara, N., Matsuda, T.: Gesture keyboard with a machine learning requiring only one camera. In: Proceedings of the 3rd Augmented Human International Conference, p. 29. ACM (2012)
Huan, D., Oggier, T., Lustenberger, F., Charbon, E.: A virtual keyboard based on true-3D optical ranging. In: Proceedings of the British Machine Vision Conference, vol. 1, pp. 220–229 (2005)
Su, X., Zhang, Y., Zhao, Q., Gao, L.: Virtual keyboard: a human-computer interaction device based on laser and image processing. In: 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), pp. 321–325. IEEE (2015)
Lee, M., Woo, W.: ARKB: 3D vision-based augmented reality keyboard. In: ICAT (2003)
Adajania, Y., Gosalia, J., Kanade, A., Mehta, H., Shekokar, N.: Virtual keyboard using shadow analysis. In: 2010 3rd International Conference on Emerging Trends in Engineering and Technology, pp. 163–165. IEEE (2010)
Posner, E., Starzicki, N., Katz, E.: A single camera based floating virtual keyboard with improved touch detection. In: 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, pp. 1–5. IEEE (2012)
Grossmann, P.: Depth from focus. Pattern Recogn. Lett. 5(1), 63–69 (1987)
Bülthoff, H.H., Mallot, H.A.: Integration of depth modules: stereo and shading. J. Opt. Soc. Am. A 5(10), 1749 (1988)
Ullman, S.: The interpretation of structure from motion. Proc. R. Soc. Lond. Ser. B Biol. Sci. 203(1153), 405–426 (1979)
Levin, A., Fergus, R., Durand, F., Freeman, W.T.: Image and depth from a conventional camera with a coded aperture. ACM Trans. Graph. 26(3), 70 (2007)
Khoshelham, K., Elberink, S.O.: Accuracy and resolution of Kinect depth data for indoor mapping applications. Sensors 12(2), 1437–1454 (2012)
Srikakulapu, V., Kumar, H., Gupta, S., Venkatesh, K.S.: Depth estimation from single image using defocus and texture cues. In: 2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), pp. 1–4. IEEE (2015)
Magoulès, F., Zou, Q.: A novel contactless human machine interface based on machine learning. In: 2017 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES), pp. 137–140. IEEE (2017)
AlKassim, Z.: Virtual laser keyboards: a giant leap towards human-computer interaction. In: 2012 International Conference on Computer Systems and Industrial Informatics. IEEE, December 2012
Salmansha, P.N., Parveen, S., Yohannan, F., Vasavan, A., Kurian, M.: Mini keyboard: portative human interactive device. In: 2017 International Conference on Communication and Signal Processing (ICCSP), pp. 1531–1535. IEEE (2017)
Goldstein, M., Chincholle, D., Backström, M.: Assessing two new wearable input paradigms: the finger-joint-gesture palm-keypad glove and the invisible phone clock. Pers. Technol. 4(2–3), 123–133 (2000)
Fukumoto, M., Tonomura, Y.: Body coupled FingerRing. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI 1997. ACM Press (1997)
Zhao, Y., Lian, C., Zhang, X., Sha, X., Shi, G., Li, W.J.: Wireless IoT motion-recognition rings and a paper keyboard. IEEE Access 7, 44514–44524 (2019)
Lv, Z., et al.: A new finger touch detection algorithm and prototype system architecture for pervasive bare-hand human computer interaction. In: 2013 IEEE International Symposium on Circuits and Systems (ISCAS 2013), pp. 725–728. IEEE (2013)
Erdem, M.E., Erdem, I.A., Atalay, V., Cetin, A.E.: Computer vision based unistroke keyboard system and mouse for the handicapped. In: 2003 International Conference on Multimedia and Expo, ICME 2003, Proceedings (Cat. No. 03TH8698), vol. 2, pp. II-765. IEEE (2003)
Srivastava, S., Tripathi, R.C.: Real time mono-vision based customizable virtual keyboard using finger tip speed analysis. In: Kurosu, M. (ed.) HCI 2013. LNCS, vol. 8007, pp. 497–505. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-39330-3_53
Livada, Č., Proleta, M., Romić, K., Leventić, H.: Beyond the touch: a web camera based virtual keyboard. In: 2017 International Symposium ELMAR, pp. 47–50. IEEE (2017)
Malik, S.: Real-time hand tracking and finger tracking for interaction csc2503f project report. Technical report, Department of Computer Science, University of Toronto (2003)
Zhuo, S., Sim, T.: Defocus map estimation from a single image. Pattern Recogn. 44(9), 1852–1858 (2011)
Subbarao, M., Surya, G.: Depth from defocus: a spatial domain approach. Int. J. Comput. Vision 13(3), 271–294 (1994)
Tang, C., Hou, C., Song, Z.: Defocus map estimation from a single image via spectrum contrast. Opt. Lett. 38(10), 1706–1708 (2013)
Karaali, A., Jung, C.R.: Edge-based defocus blur estimation with adaptive scale selection. IEEE Trans. Image Process. 27(3), 1126–1137 (2017)
Kumar, H., Gupta, S., Venkatesh, K.S.: Defocus map estimation from a single image using principal components. In: 2015 International Conference on Signal Processing, Computing and Control (ISPCC). IEEE (2015)
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Gupta, P., Goswamy, T., Kumar, H., Venkatesh, K.S. (2020). A Defocus Based Novel Keyboard Design. In: Kurosu, M. (eds) Human-Computer Interaction. Multimodal and Natural Interaction. HCII 2020. Lecture Notes in Computer Science(), vol 12182. Springer, Cham. https://doi.org/10.1007/978-3-030-49062-1_25
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