An Inertial Pen with Dynamic Time Warping Recognizer for Handwriting and Gesture Recognition

L.M.MerlinLivingston; P.Deepika; M.Benisha

doi:https://doi.org/10.14445/22315381/IJETT-V35P302

Research Article | Open Access | Download PDF

Volume 35 | Number 2 | Year 2016 | Article Id. IJETT-V35P302 | DOI : https://doi.org/10.14445/22315381/IJETT-V35P302

An Inertial Pen with Dynamic Time Warping Recognizer for Handwriting and Gesture Recognition

L.M.MerlinLivingston, P.Deepika, M.Benisha

Citation :

L.M.MerlinLivingston, P.Deepika, M.Benisha, "An Inertial Pen with Dynamic Time Warping Recognizer for Handwriting and Gesture Recognition," International Journal of Engineering Trends and Technology (IJETT), vol. 35, no. 2, pp. 506-510, 2016. Crossref, https://doi.org/10.14445/22315381/IJETT-V35P302

Abstract

This paper presents an inertial-sensorbased digital pen (inertial pen) and its associated dynamic time warping (DTW)-based recognition algorithm for handwriting and gesturer recognition. Users hold the inertial pen to write numerals or English lowercase letters and make hand gestures with their preferred handheld style and speed. The inertial signals generated by hand motions are wirelessly transmitted to a computer for online recognition. The proposed DTW-based recognition algorithm includes the procedures of inertial signal acquisition; signal preprocessing, motion detection, template selection, and recognition. We integrate signals collected from an accelerometer, a gyroscope, and a magnetometer into a quaternionbased complementary filter for reducing the integral errors caused by the signal drift or intrinsic noise of the gyroscope, which might reduce the accuracy of the orientation estimation. Furthermore, we have developed minimal intra-class to maximal inter-class based template selection method (min-max template selection method) for a DTW recognizer to obtain a superior class separation for improved recognition. Experimental results have successfully validated theeffectiveness of the DTW-based recognition algorithm for online handwriting and gesture recognition using the inertial pen.

Keywords

Inertial pen, dynamic time warping, quaternion-based complementary filter, handwriting recognition,Gesture recognition.

References

[1] K. Altun, B. Barshan, and O. Tunçel, ?Comparative study on classifying human activities with miniature inertial and magnetic sensors, PatternRecognit., vol. 43, no. 10, pp. 3605–3620, 2010.
[2] A. Akl, C. Feng, and S. Valaee, ?A novel accelerometerbased gesture recognition system, IEEE Trans. Signal Process., vol. 59, no. 12, pp. 6197–6205, Dec. 2011.
[3] W. C. Bang, W. Chang, K. H. Kang, E. S. Choi, A. Potanin, and D. Y. Kim, ?Self-contained spatial input device for wearable computers, in Proc. IEEE Int. Conf. Wearable Comput., Oct. 2003, pp. 26–34.
[4] G. Bailador, C. Sanchez-Avila, J. Guerra-Casanova, and A. de Santos Sierra, ?Analysis of pattern recognition techniques for in-air signature biometrics, Pattern Recognit., vol. 44, nos. 10–11, pp. 2468–2478, 2011.
[5] C. M. N. Brigante, N. Abbate, A. Basile, A. C. Faulisi, and S. Sessa, ?Towards miniaturization of a MEMS-based wearable motion capture system, IEEE Trans. Ind. Electron., vol. 58, no. 8, pp. 3234–3241, Aug. 2011.
[6] M. J. Caruso, ?Application of magnetoresistive sensors in navigation systems, in Proc. SAE, 1997, pp. 15–21.
[7] R. Xu, S. Zhou, and W. J. Li, ?MEMS accelerometer based nonspecificuser hand gesture recognition, IEEE Sensors J., vol. 12, no. 5, pp. 1166–1173, May 2012.
[8] Z. Dong, C. Wejinya, and W. J. Li, ?An optical-tracking calibration method for MEMS-based digital writing instrument, IEEE Sensors J., vol. 10, no. 10, pp. 1543– 1551, Oct. 2010.