Abstract
In this paper we present a system that performs automatic gesture recognition. The system consists of two main components: (i) A unified technique for segmentation and tracking of face and hands using a skin detection algorithm along with handling occlusion between skin objects to keep track of the status of the occluded parts. This is realized by combining 3 useful features, namely, color, motion and position. (ii) A static and dynamic gesture recognition system. Static gesture recognition is achieved using a robust hand shape classification, based on PCA subspaces, that is invariant to scale along with small translation and rotation transformations. Combining hand shape classification with position information and using DHMMs allows us to accomplish dynamic gesture recognition.
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References
Gupta, L., Ma, S.: Gesture-Based Interaction and Communication: Automated Classification of Gesture Contours. IEEE Transactions on Systems, Man and Cybernetics – Part C: Applications and reviews 31(1) (2001)
Chen, F.-S., Fu, C.-M., Huang, C.-L.: Hand Gesture Recognition Using a Real-time Tracking Method and Hidden Markov Models. Image and Vision Computing 21, 745–758 (2003)
Patwardhan, K.S., Dutta Roy, S.: Hand gesture modeling and recognition involving changing shapes and trajectories, using a Predictive EigenTracker, Pattern Recognition (Article in Press) (2006)
Kadir, T., Bowden, R., Ong, E.J.,, Z.: Minimal Training, Large Lexicon, Unconstrained Sign Language Recognition. In: Proc BMVC 2004, vol. 2, pp. 849–858 (2004)
Shamaie, A., Sutherland, A.: Hand Tracking in Bimanual Movements. Image and Vision Computing 23, 1131–1149 (2005)
Huang, C.-L., Jeng, S.-H.: A Model-Based Hand Gesture Recognition System. Machine Vision and Application 12(5), 243–258 (2001)
Terrillon, J.-C., Piplr, A., Niwa, Y., Yamamoto, K.: Robust Face Detection and Japanese Sign Language Hand Posture Recognition for Human-Computer Interaction in an Intelligent Room. In: Proc. Int’l Conf. Vision Interface, pp. 369–376 (2002)
Shamaie, A.: Hand Tracking and Bimanual Movement Understanding, PHD Thesis, Dublin City University (2003)
Just, A., Rodriguez, Y., Marcel, S.: Hand Posture Classification and Recognition using the Modified Census Transform. In: Proc. IEEE International Conference on Face and Gesture, pp. 351–356 (2006)
Triesch, J., Von der Malsburg, C.: Classification of hand postures against complex backgrounds using elastic graph matching. Image and Vision Computing 20, 937–943 (2002)
Yuan, Y., Barner, K.: An Active Shape Model Based Tactile Hand Shape Recognition with Support Vector Machine. In: Proc 40th Annual Conf Information Sciences and systems (2006)
Bishoff, H., Leonardis, A., Maver, J.: Multiple Eigenspaces. Pattern Recognition 35, 2613–2627 (2002)
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Coogan, T., Awad, G., Han, J., Sutherland, A. (2006). Real Time Hand Gesture Recognition Including Hand Segmentation and Tracking. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919476_50
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DOI: https://doi.org/10.1007/11919476_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48628-2
Online ISBN: 978-3-540-48631-2
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