Browse > Article
http://dx.doi.org/10.5143/JESK.2012.31.4.533

A Framework for Designing Closed-loop Hand Gesture Interface Incorporating Compatibility between Human and Monocular Device  

Lee, Hyun-Soo (School of Industrial Engineering, Kumoh National Institute of Technology (KIT))
Kim, Sang-Ho (School of Industrial Engineering, Kumoh National Institute of Technology (KIT))
Publication Information
Journal of the Ergonomics Society of Korea / v.31, no.4, 2012 , pp. 533-540 More about this Journal
Abstract
Objective: This paper targets a framework of a hand gesture based interface design. Background: While a modeling of contact-based interfaces has focused on users' ergonomic interface designs and real-time technologies, an implementation of a contactless interface needs error-free classifications as an essential prior condition. These trends made many research studies concentrate on the designs of feature vectors, learning models and their tests. Even though there have been remarkable advances in this field, the ignorance of ergonomics and users' cognitions result in several problems including a user's uneasy behaviors. Method: In order to incorporate compatibilities considering users' comfortable behaviors and device's classification abilities simultaneously, classification-oriented gestures are extracted using the suggested human-hand model and closed-loop classification procedures. Out of the extracted gestures, the compatibility-oriented gestures are acquired though human's ergonomic and cognitive experiments. Then, the obtained hand gestures are converted into a series of hand behaviors - Handycon - which is mapped into several functions in a mobile device. Results: This Handycon model guarantees users' easy behavior and helps fast understandings as well as the high classification rate. Conclusion and Application: The suggested framework contributes to develop a hand gesture-based contactless interface model considering compatibilities between human and device. The suggested procedures can be applied effectively into other contactless interface designs.
Keywords
Contactless interface; Compatibility; Classification-oriented gesture; Compatibility-oriented gesture; Handycon;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Stenger, B., Mendoca, P. R. S. and Cipolla, R., "Model-based 3D tracking of an articulated hand", Proceedings of CVRP, 2(pp. 310-315), Kauai, USA, 2001.
2 Wu, Y., Lin. J. and Huang, T. S., "Capturing natural hand articulation", Proceedings of ICCV, (pp. 426-432), USA, 2001.
3 Zhang, B. and Yun, R., "Robust gesture recognition based on distance distribution feature and skin-color segmentation", International Conference on Audio Language and Image Processing, (pp. 886-891), Nanjing, China, 2010.
4 Zhang, Q. Y., Zhang, M. Y. and Hu, J. Q., Hand gesture contour tracking based on skin color probability and state estimation model, Journal of Multimedia, 4(6), 349-355, 2009.
5 Haykin, S., Neural networks: a comprehensive foundation, 2nd Ed, Prentice Hall, 1998.
6 Lin, J., Wu, Y. and Huang, T. S., "Modeling human hand constraints", Proceedings of Human Motion, (pp. 1-6), Austin, Texas, 2000.
7 Korde, S. K. and Jondhale, K. C., "Hand gesture recognition system using standard fuzzy c-means algorithm for recognizing hand gesture with angle variations for unsupervised users", Proceedings of the 2008 First International Conference on Emerging Trends in Engineering and Technology, (pp. 681-685), Washington, DC, 2008.
8 Lee, H. and Banerjee, A., "Non-rigid body object tracking using fuzzy neural system based on multiple ROIs and adaptive motion frame method", IEEE International Conference on Systems, Man and Cybernetics, (pp. 1-6), San Antonio, Texas, 2009.
9 Lin, C. T., Chung, I. F. and Sheu, L. K. M, A neural fuzzy system for image motion estimation, Fuzzy Sets and Systems, 114(2), 281-304, 2000.   DOI
10 Lipp, J. I., "Frame-to-frame image motion estimation with a fuzzy logic system", Proceedings of the 35th Midwest Symposium on Circuit and Systems, 2(pp. 987-990), 1992.
11 Lu, S., Huang, G., Samaras, D. and Metaxas, D., "Model-based integration of visual cues for hand tracking", Proceedings of Motion and Video Computing, (pp. 118-124), Orlando, Florida, 2002.
12 Marler, R. T. and Arora, J. S., Survey of multi-objective optimization methods for engineering, Structural Multidisciplinary Optimization, 26(1), 369-395, 2004.   DOI
13 Rehg, J. M. and Kanade, T., "Model-based tracking of self-occluding articulated objects," Proceedings of ICCV, (pp. 1-6), USA, 2001.
14 Samson, N., Fink, B. and Matts, P., Interaction of skin color distribution and skin surface topography cues in the perception of female facial age and health, Journal of Cosmetic Dermatology, 10(1), 78-84, 2010.
15 Hartley, R. and Zisserman, Multiple view geometry in computer vision, 2nd Ed., Cambridge University Press, 2004.
16 Chaudhary, A., Reheja, J. L., Das, K. and Raheja, S., Intelligent Approaches to interact with machines using hand gesture recognition in natural way: a survey, International Journal of Computer Science and Engineering Survey, 2(1), 122-133, 2011.   DOI
17 Enzweiler, M., Kanter, P. and Gavrila, D. M., "Monocular pedestrian recognition using motion parallax", IEEE Intelligent Vehicles Symposium, (pp. 792-797), Eindhoven, Netherlands, 2008.
18 Garg, P., Aggarwal, N. and Sofat, S., Vision based hand gesture recognition, World Academy of Science, Engineering and Technology, 49(1), 972-977, 2009.