Abstract
The problem of hand shape classification is challenging since a hand is characterized by a large number of degrees of freedom. Numerous shape descriptors have been proposed and applied over the years to estimate and classify hand poses in reasonable time. In this paper we discuss our parallel, real-time framework for fast hand shape classification. We show how the number of gallery images influences the classification accuracy and execution time of the algorithm. We present the speedup and efficiency analyses that prove the efficacy of the parallel implementation. Different methods can be used at each step of the proposed parallel framework. Here, we combine the shape contexts with the appearance-based techniques to enhance the robustness of the algorithm and to increase the classification score. An extensive experimental study proves the superiority of the proposed approach over existing state-of-the-art methods.
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References
Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE TPAMI 24(4), 509–522 (2002)
Celebi, M.E., Aslandogan, Y.: A comparative study of three moment-based shape descriptors. In: Proc. IEEE ITCC, vol. 1, pp. 788–793 (2005)
Chapman, B., Jost, G., van der Pas, R.: Using OpenMP: Portable Shared Memory Parallel Programming. The MIT Press (2007)
Czupryna, M., Kawulok, M.: Real-time vision pointer interface. In: 2012 Proceedings of ELMAR, pp. 49–52 (2012)
Erol, A., Bebis, G., Nicolescu, M., Boyle, R.D., Twombly, X.: Vision-based hand pose estimation: A review. Comp. Vis. and Im. Underst. 108(1-2), 52–73 (2007)
Freeman, W.T., Roth, M.: Orientation histograms for hand gesture recognition. Tech. rep., MERL (1994)
Grzejszczak, T., Nalepa, J., Kawulok, M.: Real-time wrist localization in hand silhouettes. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds.) CORES 2013. AISC, vol. 226, pp. 439–449. Springer, Heidelberg (2013)
Hu, M.K.: Visual pattern recognition by moment invariants. IRE Trans. on Inf. Theory 8(2), 179–187 (1962)
Huttenlocher, D., Klanderman, G., Rucklidge, W.: Comparing images using the hausdorff distance. IEEE TPAMI 15(9), 850–863 (1993)
Kawulok, M.: Fast propagation-based skin regions segmentation in color images. In: Proc. IEEE FG, pp. 1–7 (2013)
Kawulok, M., Kawulok, J., Nalepa, J.: Spatial-based skin detection using discriminative skin-presence features. Pattern Recognition Letters 41, 3–13 (2014), http://dx.doi.org/10.1016/j.patrec.2013.08.028
Kawulok, M., Kawulok, J., Nalepa, J., Papiez, M.: Skin detection using spatial analysis with adaptive seed. In: Proc. IEEE ICIP, pp. 3720–3724 (2013)
Kawulok, M., Nalepa, J., Kawulok, J.: Skin detection and segmentation in color images. In: Celebi, M.E., Smolka, B. (eds.) Advances in Low-Level Color Image Processing, Lecture Notes in Computational Vision and Biomechanics, vol. 11, pp. 329–366. Springer Netherlands (2014), http://dx.doi.org/10.1007/978-94-007-7584-8_11
Lin, C.C., Chang, C.T.: A fast shape context matching using indexing. In: Proc. IEEE ICGEC, pp. 17–20 (2011)
MacLean, J., Pantofaru, C., Wood, L., Herpers, R., Derpanis, K., Topalovic, D., Tsotsos, J.: Fast hand gesture recognition for real-time teleconferencing applications. In: Proc. IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, pp. 133–140 (2001)
Nalepa, J., Czech, Z.J.: A parallel heuristic algorithm to solve the vehicle routing problem with time windows. Studia Informatica 33(1), 91–106 (2012)
Nalepa, J., Grzejszczak, T., Kawulok, M.: Wrist localization in color images for hand gesture recognition. In: Gruca, A., Czachórski, T., Kozielski, S. (eds.) Man-Machine Interactions 3. AISC, vol. 242, pp. 79–86. Springer, Heidelberg (2014)
Nalepa, J., Kawulok, M.: Parallel hand shape classification. In: Proc. IEEE ISM, pp. 401–402 (2013)
Papiez, M., Kawulok, M.: Adaptive skin detection in colour images using error signal space. Studia Informatica 34(2A), 365–377 (2013)
Phillips, P., Wechsler, H., Huang, J., Rauss, P.: The FERET database and evaluation procedure for face recognition algorithms. Im. and Vis. Comp. J. 16(5), 295–306 (1998)
Shen, Y., Ong, S.K., Nee, A.Y.C.: Vision-based hand interaction in augmented reality environment. Int. J. Hum. Comput. Interaction 27(6), 523–544 (2011)
Thippur, A., Ek, C.H., Kjellstrom, H.: Inferring hand pose: A comparative study of visual shape features. In: Proc. IEEE FG, pp. 1–8 (2013)
Ul Haq, E., Pirzada, S.J.H., Baig, M.W., Shin, H.: New hand gesture recognition method for mouse operations. In: 2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 1–4 (2011)
Šarić, M.: Libhand: A library for hand articulation, version 0.9 (2011), http://www.libhand.org/
Wachs, J., Stern, H., Edan, Y., Gillam, M., Feied, C., Smith, M., Handler, J.: A real-time hand gesture interface for medical visualization applications. In: Tiwari, A., Roy, R., Knowles, J., Avineri, E., Dahal, K. (eds.) App. of Soft Comp. AISC, vol. 36, pp. 153–162. Springer, Heidelberg (2006), http://dx.doi.org/10.1007/978-3-540-36266-1_15
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Nalepa, J., Kawulok, M. (2014). Fast and Accurate Hand Shape Classification. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures, and Structures. BDAS 2014. Communications in Computer and Information Science, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-06932-6_35
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DOI: https://doi.org/10.1007/978-3-319-06932-6_35
Publisher Name: Springer, Cham
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