nach oben

Erschienen in:

2016 | OriginalPaper | Buchkapitel

Manifold Learning for Hand Pose Recognition: Evaluation Framework

verfasst von : Maciej Papiez, Michal Kawulok, Jakub Nalepa

Erschienen in: Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Hand pose recognition from 2D still images is an important, yet very challenging problem of data analysis and pattern recognition. Among many approaches proposed, there have been some attempts to exploit manifold learning for recovering intrinsic hand pose features from the hand appearance. Although they were reported successful in solving particular problems related with recognizing a hand pose, there is a lack of a thorough study on how well these methods discover the intrinsic hand dimensionality. In this study, we introduce an evaluation framework to assess several state-of-the-art methods for manifold learning and we report the results obtained for a set of artificial images generated from a hand model. This will help in future deployments of manifold learning to hand pose estimation, but also to other multidimensional problems common to the big data scenarios.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Lexicon-Based System for Drug Abuse Entity Extraction from Twitter

Nächstes Kapitel A Meta-Learning Approach to Methane Concentration Value Prediction

HGR dataset is available at http://sun.aei.polsl.pl/~mkawulok/gestures.

Available at http://lvdmaaten.github.io/drtoolbox.

Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 509–522 (2002)CrossRef

Donoho, D.L., Grimes, C.: Hessian eigenmaps: locally linear embedding techniques for high-dimensional data. Proc. Nat. Acad. Sci. 100(10), 5591–5596 (2003)MathSciNetCrossRefMATH

Freeman, W.T., Roth, M.: Orientation histograms for hand gesture recognition. In: Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition, FG, pp. 296–301 (1995)

Ge, S.S., Yang, Y., Lee, T.H.: Hand gesture recognition and tracking based on distributed locally linear embedding. Image Vis. Comput. 26(12), 1607–1620 (2008)CrossRef

Grzejszczak, T., Gałuszka, A., Niezabitowski, M., Radlak, K.: Comparison of hand feature points detection methods. In: Camarinha-Matos, L.M., Barrento, N.S., Mendonça, R. (eds.) DoCEIS 2014. IFIP AICT, vol. 423, pp. 167–174. Springer, Heidelberg (2014)CrossRef

Hachaj, T., Ogiela, M.R.: Human actions recognition on multimedia hardware using angle-based and coordinate-based features and multivariate continuous hidden markov model classifier. Multimedia Tools and Applications, pp. 1–21 (in press)

Huttenlocher, D., Klanderman, G., Rucklidge, W.: Comparing images using the hausdorff distance. IEEE TPAMI 15(9), 850–863 (1993)CrossRef

Kasprowski, P.: Mining of eye movement data to discover people intentions. In: Kozielski, S., Mrozek, D., Kasprowski, P., Malysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2014. CCIS, vol. 424, pp. 355–363. Springer, Heidelberg (2014)CrossRef

Kawulok, M., Kawulok, J., Nalepa, J., Papiez, M.: Skin detection using spatial analysis with adaptive seed. In: Proceedings of the IEEE International Conference on Image Processing, ICIP 2013, pp. 3720–3724, September 2013

10.

Kawulok, M., Kawulok, J., Nalepa, J., Smolka, B.: Self-adaptive algorithm for segmenting skin regions. EURASIP J. Adv. Sig. Process. 2014(170), 1–22 (2014)

11.

Kawulok, M., Smolka, B.: Competitive image colorization. In: Proceedings of the IEEE International Conference on Image Processing, ICIP 2010, pp. 405–408 (2010)

12.

Kawulok, M., Wu, J., Hancock, E.R.: Supervised relevance maps for increasing the distinctiveness of facial images. Pattern Recogn. 44(4), 929–939 (2011)CrossRef

13.

Lee, J.A., Verleysen, M.: Nonlinear dimensionality reduction of data manifolds with essential loops. Neurocomputing 67, 29–53 (2005)CrossRef

14.

van der Maaten, L., Hinton, G.: Visualizing data using t-SNE. J. Mach. Learn. Res. 9(2579–2605), 85 (2008)MATH

15.

van der Maaten, L., Postma, E.O., Herik, H.J.: Dimensionality reduction: a comparative review. J. Mach. Learn. Res. 10(1–41), 66–71 (2009)

16.

Milligan, G.W., Cooper, M.C.: A study of the comparability of external criteria for hierarchical cluster analysis. Multivar. Behav. Res. 21(4), 441–458 (1986)CrossRef

17.

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. 81–90. Springer, Heidelberg (2014)CrossRef

18.

Nalepa, J., Kawulok, M.: Fast and accurate hand shape classification. In: Kozielski, S., Mrozek, D., Kasprowski, P., Malysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2014. CCIS, vol. 424, pp. 364–373. Springer, Heidelberg (2014)CrossRef

19.

Nalepa, J., Kawulok, M.: Adaptive memetic algorithm enhanced with data geometry analysis to select training data for SVMs. Neurocomputing 185, 113–132 (2016). http://dx.doi.org/10.1016/j.neucom.2015.12.046 CrossRef

20.

Nurzynska, K., Smolka, B.: PCA application in classification of smiling and neutral facial displays. In: Kozielski, S., Mrozek, D., Kasprowski, P., Malysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2015. CCIS, vol. 521, pp. 398–407. Springer, Heidelberg (2015)

21.

Oikonomidis, I., Kyriazis, N., Argyros, A.A.: Efficient model-based 3D tracking of hand articulations using Kinect. In: BMVC, vol. 1(2), p. 3 (2011)

22.

Roweis, S.T., Saul, L.K.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500), 2323–2326 (2000)CrossRef

23.

Starosolski, R.: New simple and efficient color space transformations for lossless image compression. J. Vis. Commun. Image Represent. 25(5), 1056–1063 (2014)CrossRef

24.

Szwoch, M.: On facial expressions and emotions RGB-D database. In: Kozielski, S., Mrozek, D., Kasprowski, P., Malysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2014. CCIS, vol. 424, pp. 384–394. Springer, Heidelberg (2014)CrossRef

25.

Tenenbaum, J.B., Silva, Vd, Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science 290(5500), 2319–2323 (2000)CrossRef

26.

Šarić, M.: Libhand: A library for hand articulation, version 0.9 (2011)

27.

Wang, Y., Luo, Z., Liu, J., Fan, X., Li, H., Wu, Y.: Real-time estimation of hand gestures based on manifold learning from monocular videos. Multimedia Tools Appl. 71(2), 555–574 (2013)CrossRef

Titel: Manifold Learning for Hand Pose Recognition: Evaluation Framework
verfasst von: Maciej Papiez
Michal Kawulok
Jakub Nalepa
Verlag: Springer International Publishing
Buch: Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery
Print ISBN: 978-3-319-34098-2

Electronic ISBN: 978-3-319-34099-9

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-34099-9_55

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner