Abstract
Gesture interaction is currently a very emerging field in computer science and engineering. This is since it is able to allow humans to communicate interactively with the machine via numerical linear algebra and mathematical techniques. In this paper, we discuss various modern state-of-the-art techniques the academic researchers including the author have attempted in recent years in order to achieve the gesture recognition and interaction in a robust way interactively. This paper is divided into three main parts. First, we introduce hand gesture recognition and body gesture recognition for general purposes using computer vision technology. These include a fast learning mechanism from an accurate six-degrees-of-freedom pose tracker, a real-time extended distance transform for the hand model, and a robust integration of support vector machine and superpixels. Second, recent gesture interaction methods, more specifically, for helping disabled people with special needs are reviewed using human-computer interaction and sensor technology. These methods include combinatorial approach recognizer (CAR), hand skeleton recognizer (HSR) and Viewpoint Feature Histogram (VFH). Third, we discuss the advantages and disadvantages of the aforementioned gesture interaction methods. By understanding the state-of-the-art approaches for computer-based gesture interaction presented recently by leading researchers, this would advance beneficially the interactions that persons with disabilities would conveniently, practically and easily have with modern recognition technology.
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References
Kılıboz, N.Ç., Güdükbay, U.: A hand gesture recognition technique for human–computer interaction. J. Vis. Commun. Image Represent. 28, 97–104 (2015). Academic Press, Inc., Orlando, FL, USA
Kerdvibulvech, C.: Hand tracking by extending distance transform and hand model in real-time. Pattern Recogn. Image Anal. 25(3), 437–441 (2015). Springer Publisher
Kim, H., Lee, S., Lee, D., Choi, S., Ju, J., Myung, H.: Real-time human pose estimation and gesture recognition from depth images using superpixels and SVM classifier. Sensors 15(6), 12410–12427 (2015). Multidisciplinary Digital Publishing Institute (MDPI)
Song, Y., Davis, R.: Continuous body and hand gesture recognition for natural human-computer interaction. In: International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, vol. 4212. AAAI Press (2015)
Kerdvibulvech, C., Yamauchi, K.: Structural human shape analysis for modeling and recognition. In: Fränti, P., Brown, G., Loog, M., Escolano, F., Pelillo, M. (eds.) S + SSPR 2014. LNCS, vol. 8621, pp. 282–290. Springer, Heidelberg (2014)
Luo, R.C., Wu, Y.-C., Lin, P.H.: Multimodal information fusion for human-robot interaction. In: Proceeding of IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics (SACI), Timisoara, Romania, pp. 535–540. IEEE Computer Society (2015)
Sempere, A.D., Serna-Leon, A., Gil, P., Puente, S., Torres, F.: Control and guidance of low-cost robots via gesture perception for monitoring activities in the home. Sensors 15(12), 31268–31292 (2015)
Premaratne, P.: Sign languages of the world. In: Human Computer Interaction Using Hand Gestures. Cognitive Science and Technology. Springer, Singapore, 174 pages, March 2014
Kirkham, R.: Forays into disability discrimination legislation and wearable computing. In: Proceeding of ACM International Symposium on Wearable Computers (ISWC), Seattle, WA, USA, 13–17 September, pp. 119–124. ACM (2014)
Gomez-Donoso, F., Cazorla, M.: Recognizing Schaeffer’s gestures for robot interaction. In: Puerta, J.M., Gomez, J.A., Dorronsoro, B., Barrenechea, E., Troncoso, A., Baruque, B., Galar, M. (eds.) Advances in Artificial Intelligence, CAEPIA’15. LNAI, vol. 9422, pp. 1045–1054. Springer (2015)
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Kerdvibulvech, C. (2016). A Review of Computer-Based Gesture Interaction Methods for Supporting Disabled People with Special Needs. In: Miesenberger, K., Bühler, C., Penaz, P. (eds) Computers Helping People with Special Needs. ICCHP 2016. Lecture Notes in Computer Science(), vol 9759. Springer, Cham. https://doi.org/10.1007/978-3-319-41267-2_70
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DOI: https://doi.org/10.1007/978-3-319-41267-2_70
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