Abstract
Current feature-based gesture recognition systems use human-chosen features to perform recognition. Effective features for classification can also be automatically learned and chosen by the computer. In other recognition domains, such as face recognition, manifold learning methods have been found to be good nonlinear feature extractors. Few manifold learning algorithms, however, have been applied to gesture recognition. Current manifold learning techniques focus only on spatial information, making them undesirable for use in the domain of gesture recognition where stroke timing data can provide helpful insight into the recognition of hand-drawn symbols. In this paper, we develop a new algorithm for multi-stroke gesture recognition, which integrates timing data into a manifold learning algorithm based on a kernel Isomap. Experimental results show it to perform better than traditional human-chosen feature-based systems.
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LaViola, J., Zeleznik, R.: Mathpad2: A system for the creation and exploration of mathematical sketches. ACM Transactions on Graphics (Proceedings of SIGGRAPH)Â 23(3) (2004)
Stahovich, T., Davis, R., Shrobe, H.: Qualitative rigid body mechanics. Artificial Intelligence (2000)
Landay, J.A., Myers, B.A.: Sketching interfaces: Toward more human interface design. IEEE Computer 34(3), 56–64 (2001)
Forbus, K.D., Usher, J., Chapman, V.: Sketching for military course of action diagrams. In: Proceedings of IUI 2003 (2003)
Do, E.Y.L.: VR sketchpad - create instant 3D worlds by sketching on a transparent window. In: de Vries, B., van Leeuwen, J.P., Achten, H.H. (eds.) CAAD Futures 2001, pp. 161–172 (July 2001)
Forsberg, A.S., Dieterich, M.K., Zeleznik, R.C.: The music notepad. In: Proceedings of UIST 1998, ACM SIGGRAPH (1998)
Igarashi, T., Matsuoka, S., Tanaka, H.: Teddy: A sketching interface for 3d freeform design. In: SIGGRAPH 1999, pp. 409–416 (August 1999)
Mahoney, J.V., Fromherz, M.P.J.: Interpreting sloppy stick figures by graph rectification and constraint-based matching. In: Fourth IAPR Int. Workshop on Graphics Recognition, Kingston, Ontario, Canada (2001)
Muzumdar, M.: ICEMENDR: Intelligent capture environment for mechanical engineering drawing. Master’s thesis, Massachusetts Institute of Technology (1999)
Hammond, T., Davis, R.: Tahuti: A geometrical sketch recognition system for UML class diagrams. In: AAAI Spring Symposium on Sketch Understanding, March 25-27, pp. 59–68 (2002)
Patel, R., Plimmer, B., Grundy, J., Ihaka, R.: Ink features for diagram recognition. In: Sketch Based Interfaces and Modeling IEEE, Eurographics (2007)
Rubine, D.: Specifying gestures by example. Computer Graphics 25(4), 329–337 (1991)
Long, A.C., Landay, J.A., Rowe, L.A., Michiels, J.: Visual similarity of pen gestures. In: Human Factors in Computing Systems (2000)
Sezgin, T.M., Stahovich, T., Davis, R.: Sketch based interfaces: Early processing for sketch understanding. In: Proceedings of 2001 Perceptive User Interfaces Workshop (PUI 2001) (2001)
Mahoney, J.V., Fromherz, M.P.J.: Three main concerns in sketch recognition and an approach to addressing them. In: AAAI Spring Symposium on Sketch Understanding, Standord, CA, pp. 105–112 (March 2002)
Rabiner, L.R., Juang, B.H.: An introduction to hidden Markov models. IEEE Trans. Acoustics, Speech, and Signal Processing Magazine 3, 4–16 (1986)
Sezgin, T.M.: Sketch Interpretation Using Multiscale Stochastic Models of Temporal Patterns. PhD thesis, Massachusetts Institute of Technology (May 2006)
Sun, Z., Jiang, W., Sun, J.: Adaptive online multi-stroke sketch recognition based on hidden markov model. In: Yeung, D.S., Liu, Z.-Q., Wang, X.-Z., Yan, H. (eds.) ICMLC 2005. LNCS, vol. 3930, pp. 948–957. Springer, Heidelberg (2006)
Muller, S., Eickeler, S., Rigoll, G.: Image database retrieval of rotated objects by user sketch. In: IEEE Workshop on Content-Based Access of Image and Video Libraries, p. 40 (1998)
Alvarado, C., Davis, R.: Sketchread: A multi-domain sketch recognition engine. In: Proceedings of UIST 2004, pp. 23–32 (2004)
Hammond, T., Davis, R.: Ladder, a sketching language for user interface developers. Elsevier, Computers and Graphics 28, 518–532 (2005)
Kara, L.B., Stahovich, T.F.: An image-based trainable symbol recognizer for sketch-based interfaces. In: Making Pen-Based Interaction Intelligent and Natural, Menlo Park, California, October 21-24. AAAI Fall Symposium, pp. 99–105 (2004)
Lee, W., Kara, L.B., Stahovich, T.F.: An efficient graph-based recognizer for hand-drawn symbols. Computers & Graphics 31, 554–567 (2007)
Seung, H.S., Lee, D.D.: The manifold ways of perception. Science 290, 2268–2269 (2000)
Tenenbaum, J.B., de Silva, V., Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science 290, 2319–2323 (2000)
Saul, L., Roweis, S.T.: Think globally, fit locally: Unsupervised learning of low dimensional manifolds. Journal of Machine Learning Research 4, 119–155 (2003)
Belkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation 15, 1373–1396 (2003)
de Silva, V., Tenenbaum, J.B.: Global versus local methods in nonlinear dimensionality reduction. In: Advances in Neural Information Processing Systems, vol. 15, pp. 705–712. MIT Press, Cambridge (2003)
Jenkins, O.C., Matari, M.J.: A spatio-temporal extension to isomap nonlinear dimension reduction. In: Proc. Int’l. Conf. Machine Learning, Banff, Canada (2004)
Wobbrock, J., Wilson, A., Li, Y.: Gestures without libraries, toolkits, or training: A $1 recognizer for user interface prototypes. In: Proc. of the 20th Annual ACM Symposium on User Interface Software and Technology, Newport, RI, USA (2007)
Choi, H., Choi, S.: Robust Kernel Isomap. Pattern Recognition 40(3), 853–862 (2007)
Girolaini, M.: Mercer kernel-based clustering in feature space. IEEE Transactions on Neural Networks 13(3), 780–784 (2002)
Schölkopf, B., Smola, A.J., Müller, K.R.: Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation 10(5), 1299–1319 (1998)
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Choi, H., Paulson, B., Hammond, T. (2008). Gesture Recognition Based on Manifold Learning. In: da Vitoria Lobo, N., et al. Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2008. Lecture Notes in Computer Science, vol 5342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89689-0_29
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