nach oben

Erschienen in:

2017 | OriginalPaper | Buchkapitel

An Evaluation of Hand Pyramid Structure for Hand Representation Based on Kernels

verfasst von : Van-Toi Nguyen, Thi-Lan Le, Thanh-Hai Tran

Erschienen in: Advances in Information and Communication Technology

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 posture recognition is an active research topic in computer vision and robotics with many applications ranging from automatic sign language recognition to human-system interaction. Recently, we have proposed a new descriptor for hand representation based on the kernel method (KDES) [1]. Our new descriptor inherits the main idea of KDES but we proposed three improvements to make it more robust. One of the improvements was that we introduced a new hand pyramid structure [14]. Intuitively, hand pyramid is more suitable to hand structure than conventional pyramid. In our previous work, we have demonstrated that the combination of improvements to KDES gives more accurate hand posture classification than using original KDES. However, it still lacks discussions and experimental evidences of the contribution of hand pyramid for hand representation. In this paper, we build specific hand dataset and conduct more experiments to show how hand pyramid contributes for hand representation. We will discuss deeply on the results and analyze the impact of this pyramid on hand posture classification.

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 Adaptive Robust Ability of High Order Sliding Mode Control for a 3-D Overhead Crane System

Nächstes Kapitel An Evolutionary-Based Term Reduction Approach to Bilingual Clustering of Malay-English Corpora

Bo, L., et al.: Kernel descriptors for visual recognition. In: NIPS, pp. 1–9 (2010)

Bo, L., Sminchisescu, C.: Efficient match kernel between sets of features for visual recognition. In: NIPS, pp. 1–9 (2009)

Boughnim, N., Marot, J.: Hand posture recognition using jointly optical flow and dimensionality reduction. EURASIP J. Adv. Sig. Process. 2013, 1–22 (2013)CrossRef

Chaudhary, A., et al.: Intelligent approaches to interact with machines using hand gesture recognition in natural way: a survey. IJCSES 2(1), 122–133 (2011)CrossRef

Choi, J., Seo, B.: Robust hand detection for augmented reality interface. In: Proceedings of the 8th International Conference on Virtual Reality Continuum and its Applications in Industry, pp. 319–322 (2009)

Dardas, N.H., Georganas, N.D.: Real-time hand gesture detection and recognition using bag-of-features and support vector machine techniques. IEEE Trans. Instrum. Meas. 60(11), 3592–3607 (2011)CrossRef

Francke, H., Ruiz-del-Solar, J., Verschae, R.: Real-time hand gesture detection and recognition using boosted classifiers and active learning. In: Mery, D., Rueda, L. (eds.) PSIVT 2007. LNCS, vol. 4872, pp. 533–547. Springer, Heidelberg (2007). doi:10.1007/978-3-540-77129-6_47 CrossRef

Freeman, W.T., Roth, M.: Orientation histograms for hand gesture recognition. In: International Workshop on Automatic Face and Gesture Recognition, pp. 296–301 (1995)

Gupta, S., et al.: Static hand gesture recognition using local gabor filter. Procedia Eng. 41, 827–832 (2012). IrisCrossRef

10.

Hasan, M.M., Mishra, P.K.: Hand gesture modeling and recognition using geometric features : a review. CJIPCV 3, 1 (2012)

11.

Kaufmann, B., Louchet, J., Lutton, E.: Hand posture recognition using real-time artificial evolution. In: Chio, C., Cagnoni, S., Cotta, C., Ebner, M., Ekárt, A., Esparcia-Alcazar, A.I., Goh, C.-K., Merelo, J.J., Neri, F., Preuß, M., Togelius, J., Yannakakis, G.N. (eds.) EvoApplications 2010. LNCS, vol. 6024, pp. 251–260. Springer, Heidelberg (2010). doi:10.1007/978-3-642-12239-2_26 CrossRef

12.

Lockton, R., Fitzgibbon, A.W.: Real-time gesture recognition using deterministic boosting. In: BMVC, pp. 817–826 (2002)

13.

Marcel, S., Bernier, O.: Hand posture recognition in a body-face centered space. In: Braffort, A., Gherbi, R., Gibet, S., Teil, D., Richardson, J. (eds.) GW 1999. LNCS (LNAI), vol. 1739, pp. 97–100. Springer, Heidelberg (1999). doi:10.1007/3-540-46616-9_9 CrossRef

14.

Nguyen, V.-T., et al.: A new hand representation based on kernels for hand posture recognition. In: The 11th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2015) (2015)

15.

Nguyen, V.-T.: Visual interpretation of hand postures for human-machine interaction (2015)

16.

Ong, E.-J., Bowden, R.: A boosted classifier tree for hand shape detection. In: Sixth IEEE International Conference on Face and Gesture Recognition, pp. 889–894 (2004)

17.

Pavlovic, V.I., et al.: Visual interpretation of hand gestures for human-computer interaction: a review. TPAMI 19(7), 677–695 (1997)CrossRef

18.

Rautaray, S.S., Agrawal, A.: Vision based hand gesture recognition for human computer interaction: a survey. AIR 43, 1–54 (2012)

19.

Sgouropoulos, K., et al.: A dynamic gesture and posture recognition system. J. Intell. Robot. Syst. 76(2), 283–296 (2013)CrossRef

20.

Stergiopoulou, E., Papamarkos, N.: Hand gesture recognition using a neural network shape fitting technique. EAAI 22(8), 1141–1158 (2009)

21.

Tran, T-T-H Nguyen, T-T-M : Invariant lighting hand posture classification. In: IEEE International Conference on Progress in Informatics and Computing (PIC), pp. 827–831 (2010)

22.

Wachs, J., et al.: A real-time hand gesture system based on evolutionary search. In: GECCO2005: Tenth Genetic and Evolutionary Computation Conference, Washington, DC, USA (2005)

23.

Wu, Y., Huang, T.S.: View-independent recognition of hand postures. In: Computer Vision and Pattern Recognition, pp. 88–94 (2000)

Titel: An Evaluation of Hand Pyramid Structure for Hand Representation Based on Kernels
verfasst von: Van-Toi Nguyen
Thi-Lan Le
Thanh-Hai Tran
Verlag: Springer International Publishing
Buch: Advances in Information and Communication Technology
Print ISBN: 978-3-319-49072-4

Electronic ISBN: 978-3-319-49073-1

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-49073-1_15

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"