Abstract
Recently several optical and non-optical sensors based gesture recognition techniques have been developed to interact with computing devices. However, these techniques mostly suffer from problems such as occlusion and noise. In this work, we present Pingu, a multi-sensor based framework that is capable of recognizing simple, sharp, and tiny gestures without the problems mentioned above. Pingu has been calibrated in the form of a wearable finger ring, capable of interacting even when the device is not in the vicinity of the user. An advanced set of sensors, wireless connectivity, and feedback facilities enable Pingu for a wide range of potential applications, from novel gestures to social computing. In this paper, we present our results based on experiments conducted to explore Pingu’s use as a general gestural interaction device. Our analysis, based on simple machine learning algorithms, shows that simple and sharp gestures performed by a finger can be detected with a high accuracy, thereby, stablishing Pingu as a wearable ring to control a smart environment effectively.
Chapter PDF
Similar content being viewed by others
References
Mistry, P., Maes, P.: SixthSense: A wearable gestural interface. In: ACM SIGGRAPH ASIA 2009 Sketches. ACM (2009)
Starner, T., et al.: The gesture pendant: A self-illuminating, wearable, infrared computer vision system for home automation control and medical monitoring. In: The Fourth International Symposium on Wearable Computers. IEEE (2000)
Butler, A., Izadi, S., Hodges, S.: SideSight: Multi- “touch” interaction around small devices. In: Proc. UIST, pp. 201–204 (2008)
Ketabdar, H., Yüksel, K.A., Roshandel, M.: MagiTact: Interaction with mobile devices based on compass (magnetic) sensor. In: Proceedings of the 15th International Conference on Intelligent User Interfaces. ACM (2010)
Ashbrook, D., Baudisch, P., White, S.: Nenya: Subtle and eyes-free mobile input with a magnetically-tracked finger ring. In: Proceedings of the 2011 Annual Conference on Human Factors in Computing Systems. ACM (2011)
Ketabdar, H., Moghadam, P., Roshandel, M.: Pingu: A new miniature wearable device for ubiquitous computing environments. In: 2012 Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS). IEEE (2012)
Wu, J., Pan, G., Zhang, D., Qi, G., Li, S.: Gesture recognition with a 3-d accelerometer. In: Zhang, D., Portmann, M., Tan, A.-H., Indulska, J. (eds.) UIC 2009. LNCS, vol. 5585, pp. 25–38. Springer, Heidelberg (2009)
Fukumoto, M., Tonomura, Y.: “Body coupled FingerRing”: wireless wearable keyboard. In: Proceedings of the SIGCHI Conference on Human Factors in Computing systems. ACM (1997)
Kim, J., et al.: The gesture watch: A wireless contact-free gesture based wrist interface. In: 2007 11th IEEE International Symposium on Wearable Computers. IEEE (2007)
Card, S.K., Mackinlay, J.D., Robertson, G.G.: A morphological analysis of the design space of input devices. ACM Trans. Inf. Syst. 9(2), 99–122 (1991)
Perng, J.K., Fisher, B., Hollar, S., Pister, K.S.J.: Acceleration sensing glove (ASG). In: The Third International Symposium on Wearable Computers (ISWC 1999), pp. 178–180 (1999)
Loclair, C., Gustafson, S., Baudisch, P.: PinchWatch: A wearable device for one-handed microinteractions. In: Proc. MobileHCI (2010)
Jing, L., et al.: Magic Ring: A Finger-worn device for multiple appliances control using static finger gestures. Sensors 12(5), 5775–5790 (2012)
Weka3: Data Mining Software in Java, http://www.cs.waikato.ac.nz/ml/weka/
Witten, I.H., Frank, E., Hall, M.A.: Data Mining: Practical Machine Learning Tools and Techniques: Practical Machine Learning Tools and Techniques. Morgan Kaufmann (2011)
Ketabdar, H., Moghadam, P., Naderi, B., Roshandel, M.: Magnetic signatures in air for mobile devices. In: Mobile HCI 2012, pp. 185–188 (2012)
Ketabdar, H., Abolhassani, A.H., Roshandel, M.: MagiThings: Gestural Interaction with Mobile Devices Based on Using Embedded Compass (Magnetic Field) Sensor. IJMHCI 5(3), 23–41 (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Roshandel, M., Munjal, A., Moghadam, P., Tajik, S., Ketabdar, H. (2014). Multi-sensor Based Gestures Recognition with a Smart Finger Ring. In: Kurosu, M. (eds) Human-Computer Interaction. Advanced Interaction Modalities and Techniques. HCI 2014. Lecture Notes in Computer Science, vol 8511. Springer, Cham. https://doi.org/10.1007/978-3-319-07230-2_31
Download citation
DOI: https://doi.org/10.1007/978-3-319-07230-2_31
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07229-6
Online ISBN: 978-3-319-07230-2
eBook Packages: Computer ScienceComputer Science (R0)