Application of the Device of Measurement of Bioelectric Activity of Muscles and Nerve Structures for Gesture Recognition - Application of Gesture Recognition on the Example of Action Game
Levanov Alexey Alexendrovich
2013
Abstract
Using the device bioPlux we can identify a set of user gestures, and based on them to create a multimodal interface. Gestures are selected so that they are not dependent on each other. The main goal of the research is to create a simple game which can be controlled by using different hand movements. Relevance of the topic from the practical point of view is determined by the need to create a software system that can use sign language interface in real time.
References
- Alon, J., Athistos, V., Yuan, Q., and Sclaroff S. (2005). Simultaneous Localization and Recognition of Dynamic Hand Gestures. Proc. of WACV MOTION'05, 2, 254-260.
- Avilts-Aniaga, H., H., Sucart, L., E., and Mendozaz, C., E. (2003). Visual Gesture Recognitions Using Dynamic Naive Bayesian Classifiers. Proc. of IEEE Internat. Workshop on Robot and Human Interac. Com.- Milibrae, 133-138.
- Bobick, A. F., & Wilson, A. D. (1997). A State-Based Approach to the Representation and Recognition of Gesture. Proc. of IEEE Transactions on pattern analysis and machine intelligence, 19(12), 1325-1337.
- Brown, L., G. (1992). A Survey of Image Registration Techniques. Computing Surveys, 24(4), 325-376.
- Umpire Gesture Recognition. Structural, Syntactic, and Stat. Pat. Recog., Vol. 3138, pp. 859-867.
- Cutler, R., & Turk, M. (1998). View-based Interpretation of Real-time Optical Flow for Gesture Recognition. Proc. of Third IEEE Intern. Conf. on Autom. Face and Gesture Recog. Nara, 416-421.
- Darwiche, A. A. (2001). Differential Approach to Inference in Bayesian Networks. Journal of the ACM, 50(3), 280 -305.
- Davis, J.W., & Shah, M. (1992). Gesture Recognition. Proc. of European Conf. Comp. Vis., 331-340.
- Devyatkov, V. & Alfimtsev, A. (2008). Optimal Fuzzy Aggregation of Secondary Attributes in Recognition Problems. Proc. of 16-th International Conference in Central Europe on Computer Graphics. Visualization and Computer Vision. Plzen, 78-85.
- Devyatkov, V., & Alfimtsev, A. (2009). Dynamic Gesture Recognition Using Fuzzy Model. Proc. of the 13th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI 2009).-Orlando, USA.- p. 145-150.
- Ekman,P., & Friesen,W. (1969). The Repertoire of Nonverbal Behavior: Categories, Origins, Usage and Coding. Semiotica, 1, 49-98.
- Freeman, W.T., Tanaka, K., Ohta, J., Kyuma K. (1996). Computer Vision for Computer Games. In Proc. IEEE Int. Conf. on Face & Gesture Recognition, 100-105.
- Frei, W., & Chen, C. C. (1977). Fast Boundary Detection: A Generalization and New Approach. IEEE Trans. Comput., 26(10), 988-998.
- Garcia, C., & Tziritas, G. (1999). Face Detection Using Quantized Skin Color Regions Merging and Wavelet Packet Analysis. IEEE Transactions on multimedia, 1(3), 264-277.
- Gould, K., & Shah, M. (1989). The Trajectory Primal Sketch: A MultiScale Scheme for Representing Motion Characteristics. Proc. of Comp. Vis. and Pattern Rec, 79-85.
- Schunck, B. (1998). Determining Optical Flow. Artificial Intelligence, 17, 185-203.
- Johansson, G. (1964) Perception of Motion and Changing Form. Scandanavian J. Psychology, 5, 181-208.
- Kang, H., Lee, C. W., Jung, K. (2004) Recognition-Based Gesture Spotting in Video Games. Pattern Rec. Let., V. 25, I. 15, 1701-1714.
- Keir, P. Elgoyhen, J. Naef, M. Payne, J. Horner, M. Anderson, P. (2006). Gesture-Recognition with Nonreferenced Tracking. 1st IEEE Symposium on 3D User interfaces, 137.
- Kirsch, R. (1977). Computer Determination of the Constituent Structure of Biological Images. Comput. Biomed, 4(3), 315-328.
- Kim, N., An, Y., Cha B. (2009). Gesture Recognition Based on Neural Networks for Dance Game Contents. International Conference on New Trends in Information and Service Science, 134-1139.
- Kwak, K., & Pedrycz, W. (2005). Face Recognition: A Study in Information Fusion Using Fuzzy Integral. Patt. Recog. Lett, 26, 719-733.
- Kyle, J. & Woll B. (1988) Sign Language: The Study of deaf People and Their Language. Cambridge University Press, 328 p.
- Lienhart, R., & Maydt J. (2002). An Extended Set of Haar-like Features for Rapid Object Detection. IEEE ICIP, 1, 900-903.
- Lienhart, R., Kuranov, A., Pisarevsky, V. (2003). Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection. Proc. of DAGM03, 297-304.
- Liu, Z. (2001). Dynamic Image Sequence Analysis Using Fuzzy Measures. IEEE trans. on sys., man, and cybern, 31(4), 557-572.
- Mamiya, H., Sato, T., Fukuchi, K., Koike, H. (2007) A Tabletop Entertainment System and Finger Tapping Gesture Recognition. In Proceedings of WISS, JSSST, 53-58.
- Miklós, I., & Meyer, I. (2005) A Linear Memory Approach for Baum-Welch Training. BMC Bioinformatics, 6(231), 1471-2105.
- Nishikawa, A., Hosoi, T., Koara, K., Negoro, D., Hikita, A., Asano, S., Kakutani, H., Miyazaki, F., Sekimoto, M., Yasui, M., Miyake, Y., Takiguchi, S., and Monden, M. (2003). FAce MOUSe: A Novel HumanMachine Interface for Controlling the Position of a Laparoscope. IEEE Trans on Robotics and Automation 19:5:825-841.
- Ong, S., & Ranganath, S. (2005). Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 5(6), 873-891.
- Park, J. Y., Yi, J. H. (2008). Gesture Recognition Based Interactive Boxing Game. Scientific Literature Digital Library: http://www.icis.ntu.edu.sg/scs-ijit/1207/ijit1207_05.pdf
- Patel, S. (1995). A lower-complexity Viterbi approach. Acoustics, Speech, and Signal Processing, 1, 592-595.
- Rabiner, L., & Juang, B.H. (1993). Fundamentals of Speech Recognition. Prentice Hall.
- Rett, J., & Dias, J. (2006). Gesture Recognition Using a Marionette Model and Dynamic Bayesian Networks. Lecture notes in computer science, 4142, 69-80.
- Rigoll, G., Kosmala, A., and Eickeler, S. (1997). High Performance Real-Time Gesture Recognition Using Hidden Markov Models. Proc. of the Internat. Gesture Workshop on Gesture and Sign Lang. in HumanComputer Interac, 69-80.
- Russel, S.J., & Norvig, P. (2002). Artificial Intelligence. A modern approach. Upper Saddle River/new Jersey, Prentice Hall.
- Sandberg, A. (1997). Gesture Recognition using Neural Networks. Master thesis. Stockholm.
- Schultz M, Gill J, Zubairi S, Huber R, Gordin F (2003) Bacterial Contamination of Computer Keyboards in a Teaching Hospital. Infect Control Hosp Epidemiol 24:302-303
- Schumeyer, R. P., & Barner, K. E. (1998). A Color-Based Classifier for Region Identification in Video. SPIE Visual Communications Image Processing, 3309, 189- 200.
- Shapiro, L.G., & Stockman, G.S. (2001). Computer Vision. Upper Saddle River, N.J., Prentice-Hall.
- Sharma, R. (2003). Speech-Gesture Driven Multimodal Interfaces for Crisis Management. Proc. of the IEEE, 91, 1327-1354.
- Sigal, L., & Sclaroff S. (2004). Skin Color-Based Video Segmentation under Time-Varying Illumination. IEEE Transactions on pattern analysis and machine intelligence, 26(7), 862-877.
- Silva, M., Courboulay, V., Prigent, A., Estraillier, P. (2008). Real-Time Face Tracking for Attention Aware Adaptive Games. ICVS 2008, 99-108.
- Starner, T., Weaver, J., and Pentland, A. (1998). RealTime American Sign Language Recognition Using Desk and Wearable Computer Based Video. IEEE Trans. Pattern Analysis and Machine Intelligence, 20(12), 1371-1375.
- Song, P., Yu, H., Winkler, S. (2009). Vision-based 3D Finger Interactions for Mixed Reality Games with Physics Simulation. The International Journal of Virtual Reality, 8(2):1-6.
- Su, J., & Zhang, H. (2005). Full Bayesian Network Classifiers. Proc. of the 23rd international conference on Machine learning, 897 - 904.
- Tahani, H., & Keller, J. M. (1990). Information Fusion in Computer Vision Using the Fuzzy Integral. IEEE transactions on systems, man, and cybernetics, 20(3), 733-741.
- Tomasi, C., Petrov, S., and Sastry, A. (2003). 3D Tracking = Classification + Interpolation. Proc. of Int. Conf. Computer Vision, 1441-1448.
- Viola, P., & Jones, M. (2001) Rapid Object Detection using a Boosted Cascade of Simple Features. IEEE CVPR, 1, 511-518.
- Winkler, S., Yu, H., Zhou, Z.Y. (2007). Tangible Mixed Reality Desktop for Digital Media Management. In SPIE Engineering Reality of Virtual Reality, Vol. 6490B.
- Winstone, P.G. (1992). Artificial Intelligence. Reading/Massachusetts, Addison-Wesley Publishing Company.
- Wong, S.F., & Cipolla, R. (2006). Continuous Gesture Recognition using a Sparse Bayesian Classifier. Proc of 18th Internat. Conf. on Pattern Recognition, 1084- 1087.
- Wu, H., Chen, Q., and Yachida, M. (1999). Face Detection From Color Images Using a Fuzzy Pattern Matching Method. IEEE Transactions on pattern analysis and machines intelligence, 21(6), 557-563.
- Yamato, J., Ohya, J., and Ishii, K. (1992). Recognizing Human Action in Time-Sequential Images Using Hidden Markov Model. Proc. of Comp. Vis. and Pattern Rec, 379-385.
- Waibel, A. (1996) A Real-Time Face Tracker. Proc. of the Third IEEE Workshop on Applicat. of Comp. Vision, 142-147.
- Ye, G., Corso, J., Hager, G., (2004). Gesture Recognition Using 3D Appearance and Motion Features. Proc. of Workshop on Real-time Vision for Human-Computer Interaction, 160-161.
- Zeng, T., J., Wang, Y., Freedman, M., T., and Mun, S., K. (1997). Finger Tracking for Breast Palpation Quantification Using Color Image Features. SPIE Optical Eng., 36(12), 3455-3461
Paper Citation
in Harvard Style
Alexendrovich L. (2013). Application of the Device of Measurement of Bioelectric Activity of Muscles and Nerve Structures for Gesture Recognition - Application of Gesture Recognition on the Example of Action Game . In Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: MHGInterf, (BIOSTEC 2013) ISBN 978-989-8565-34-1, pages 301-305. DOI: 10.5220/0004365803010305
in Bibtex Style
@conference{mhginterf13,
author={Levanov Alexey Alexendrovich},
title={Application of the Device of Measurement of Bioelectric Activity of Muscles and Nerve Structures for Gesture Recognition - Application of Gesture Recognition on the Example of Action Game},
booktitle={Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: MHGInterf, (BIOSTEC 2013)},
year={2013},
pages={301-305},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004365803010305},
isbn={978-989-8565-34-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: MHGInterf, (BIOSTEC 2013)
TI - Application of the Device of Measurement of Bioelectric Activity of Muscles and Nerve Structures for Gesture Recognition - Application of Gesture Recognition on the Example of Action Game
SN - 978-989-8565-34-1
AU - Alexendrovich L.
PY - 2013
SP - 301
EP - 305
DO - 10.5220/0004365803010305