Narzędzia help

Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
first previous next last
cannonical link button


Elektronika : konstrukcje, technologie, zastosowania

Tytuł artykułu

Gesture-based computer control system

Autorzy Lech, M.  Kostek, B.  Czyżewski, A.  Odya, P. 
Treść / Zawartość
Warianty tytułu
EN System sterowania komputerem za pomocą gestów
Języki publikacji PL
PL W artykule przedstawiono system sterowania komputerem za pomocą gestów rąk. W pierwszej części dokonano przeglądu wybranych metod rozpoznawania gestów. Następnie zaprezentowano część sprzętową systemu oraz metodykę sterowania. Opisano również architekturę oprogramowania wraz z metodami i algorytmami zastosowanymi przy rozpoznawaniu gestów rąk. W dalszej części pokazano zestaw prostych gestów oraz bazujących na nich gestów złożonych, rozpoznawanych przez system.
EN In the paper a system for controlling computer applications by hand gestures is presented. First, selected methods used for gesture recognition are described. The system hardware and a way of controlling a computer by gestures are described. The architecture of the software along with hand gesture recognition methods and algorithms used are presented. Examples of basic and complex gestures recognized by the system are given.
Słowa kluczowe
PL rozpoznawanie gestów   przetwarzanie obrazów   interakcja człowiek-komputer  
EN gesture recognition   image processing   human-computer interaction  
Wydawca Wydawnictwo SIGMA-NOT
Czasopismo Elektronika : konstrukcje, technologie, zastosowania
Rocznik 2010
Tom Vol. 51, nr 3
Strony 49--53
Opis fizyczny Bibliogr. 21 poz., tab.
autor Lech, M.
autor Kostek, B.
autor Czyżewski, A.
autor Odya, P.
  • Gdansk University of Technology, Multimedia Systems Dept., Gdansk
[1] Birk J., Kelley R., Chen N., Wilson L.: Image Feature Extraction Using Diameter-Limited Gradient Direction Histograms. Pattern Analysis and Machine Intelligence. IEEE Transactions on, Vol. PAMI-1, issue 2, April 1979, pp. 228-235.
[2] Clipp B., Welch G., Frahm J., Pollefeys M.: Structure From Motion via a Two-Stage Pipeline of Extended Kalman Filters Proceedings of the British Machine Vision Conference (BMVC 2007), September 10-13 2007.
[3] Dayong Zhou, DeBrunner V. E.: Efficient adaptive Volterra filters for active nonlinear noise control with a linear secondary-path Circuits and Sygtems, 2004.ISCAS'04. Proceedings of the 2004 International Symposium on, vol. 3, 23-26 May 2004, pp. III - 299-300.
[4] Da-Rui Sun, Le-Nan Wu: A local-to-holistic face recognition approach using elastic graph matching Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on, vol. 1, 4-5 Nov. 2002, pp. 240-242.
[5] Giorgino T.,Tormene P., Quaglini S.: A Multivariate Time-Warping Based Classifier for Gesture Recognition with Wearable Strain Sensors. Engineering in Medicine and Biology Society. 2007. EMBS 2007. 29th Annual International Conference of the IEEE. 26 Aug. 2007. 22 - pp. 4903-4906.
[6] Morguet P., Lang M.: Spotting dynamic hand gestures in video image sequences using hidden Markov models, Image Processing. 1998. ICIP 98. Proceedings. 1998 International Conference on, 4-7 Oct. 1998, vol. 3, pp. 193-197.
[7] Muscillo R., Conforto S., Schmid M., Caselli P., D'Alessio T.: Classification of Motor Activities through Derivative Dynamic Time Warping applied on Accelerometer Data. Engineering in Medicine and Biology Society. 2007. EMBS 2007. 29 th Annual International Conference of the IEEE, 22-26 Aug. 2007, pp. 4930-1933.
[8] Kenji Nakayama, Akihiro Hirano, Hiroaki Kashimoto: A Lattice Predictor Based Adaptive Volterra Filter and a Synchronized Learning Algorithm, XII European Signal Processing Conference, Vienna, 2004.
[9] Lech M., Kostek B., Czyzewski A., Odya P.: Gesture Recognition Framework for Multimedia Content Viewer Controlling, Proceedings of the 13 th IEEE SPA Conference on Signal Processing - Algorithms, Architectures, Arrangements, and Applications, 2009.
[10] Pinheiro, A. M. G.: Image Description Using Scale-Space Edge Pixel Directions Histogram, Semantic Media Adaptation and Personalization, Second International Workshop on, 17-18 Dec. 2007, pp. 211-218.
[11] Qiuyu Zhang, Fan Chen, Xinwen Liu: Hand Gesture Detection and Segmentation Based on Difference Background Image with Complex Background, Embedded Software and Systems. 2008. ICESS'08. Intemational Conference on, 29-31 July 2008, pp. 338-343.
[12] Stamou G. N., Nikolaidis, Pitas I.: Object tracking based on morphological elastic graph matching, Image Processing. 2005. ICIP 2005. IEEE International Conference on, vol. 1, 11-14 Sept. 2005. pp. I - 709-12.
[13] St-Pierre M., Gingras D.: Comparison between the unscented Kalman filter and the extended Kalman filter for the position estimation module of an integrated navigation information system, Intelligent Vehicles Symposium. 2004 IEEE, 14-17 June 2004, pp. 831-835.
[14] Sundaramoorthi G., Jackson J. D., Yezzi A., Mennucci A. C.: Tracking With Sobolev Active Contours, Computer Vision and Pattern Recognition. 2006 IEEE Computer Society Conference on, Volume 1, 17-22 June 2006, pp. 674-680.
[15] Sundaramoorthi G., Yezzi A., Mennucci A. C.: Coarse-to-Fine Segmentation and Tracking Using Sobolev Active Contours, Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 30, Issue 5. May 2008, pp. 851-864.
[16] Welch G.: HISTORY: The Use of the Kalman Filter for Human Motion Tracking in Virtual Reality, Presence: Teleoperators and Virtual Environments. 18 (1), 2009.
[17] Welch G., Bishop G.: An Introduction to the Kalman Filter. SIGGRAPH 2001 course 8. In Computer Graphics, Annual Conference on Computer Graphics & Interactive Techniques, ACM Press, August 12-17 2001.
[18] Xun Wang, Lei He, Yingjie Tang, Wee W. G.: A divide and conquer deformable contour method with a model based searching algorithm, Systems. Man, and Cybernetics. Part B. IEEE Transactions on, vol. 33, Issue 5. Oct. 2003, pp. 738-751
[19] Yang H., Welch G.: Model-Based 3D Object Tracking Using an Extended-Extended Kalman Filter and Graphics Rendered Measurements. In Proceedings of 1st Computer Vision for Interactive and Intelligent Environments (CV4IIE) workshop, 2005
[20] Yaniv R., Burshtein D.: An enhanced dynamic time warping model for improved estimation of DTW parameters. Speech and Audio Processing. IEEE Transactions on. vol. 11, Issue 3. May 2003, pp. 216-228.
[21] Zafeiriou S., Tefas A., Pitas I.: Advances in Elastic Graph Matcriing for Frontal Face Verification. Computational Intelligence in Image and Signal Processing. 2007. CIISP 2007. IEEE Symposium on. 1-5 April 2007, pp. 319-324.
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-article-BWA9-0036-0010