Random Articles
Reseach Article
Implementation of Low Cost Human Machine Interface (HMI) using Natural Feature Tracking (NFT)
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 86 - Number 17 |
| Year of Publication: 2014 |
| Authors: Krishna Chauhan, Sandeep Singh Padan |
10.5120/15077-3456
|
Krishna Chauhan, Sandeep Singh Padan . Implementation of Low Cost Human Machine Interface (HMI) using Natural Feature Tracking (NFT). International Journal of Computer Applications. 86, 17 ( January 2014), 18-21. DOI=10.5120/15077-3456
Abstract
This paper introduces an altogether a new, easy and user friendly approach for detection and tracking of the natural features such as a human finger in its natural form without the use of any added on artificial reference. The natural features are used to stabilize tracking process against external disturbances, noise or any occlusions. This paper emphasizes on integration of various technological concepts offering users a new and cheap way of studying & experiencing user friendly recognition of natural features without the need of any external and expensive hardware or software.
References
- Lim, M. J. , Jung, H. W. , Lee, K. Y. : Game-type recognition rehabilitation system based on augmented reality through object understanding. The Journal of the Institute of Webcasting, Internet and Telecommunication 11(3) (2011) 93–98
- Lucas, B. , Kanade, T. : An iterative image registration technique with an application to stereo vision. In: Proceedings of the 7th International Joint Conference on Artificial Intelligence. (1981) 674–679
- Q. Cai, D. Gallup, C. Zhang, and Z. Zhang. 3d deformable face tracking with a commodity depth camera. In Proc. of IEEE ECCV, 2010.
- J. Shotton, A. Fitzgibbon, and etc. Real-time human pose recognition in parts from single depth images. In Proc. Of IEEE CVPR, 2011.
- Rafiqul Zaman Khan1 & Noor Adnan Ibraheem, (2012) "Survey on Gesture Recognition for Hand Image Postures", International Journal of Computer and Information Science, Vol. 5, No. 3, pp 110- 121. doi:10. 5539/cis. v5n3p110
- Joseph J. LaViola Jr. (1999) "A Survey of Hand Posture and Gesture Recognition Techniques and Technology", Master Thesis, NSF Science and Technology Center for Computer Graphics and Scientific Visualization, USA.
- Thomas B. Moeslund & Erik Granum (2001) "A Survey of Computer Vision-Based Human Motion Capture," Elsevier, Computer Vision and Image Understanding, Vol. 81, pp 231 268.
- T. R. Trigo & S. R. M. Pellegrino, (2010) "An Analysis of Features for Hand-Gesture Classification", 17th International Conference on Systems, Signals and Image Processing (IWSSIP 2010), pp 412-415
- Luigi Lamberti & Francesco Camastra, (2011) "Real-Time Hand Gesture Recognition Using a Color Glove", Springer 16th international conference on Image analysis and processing: Part I (ICIAP'11), pp 365-373.
- Mokhtar M. Hasan, and Pramod K. Mishra, (2012) "Hand Gesture Modeling and Recognition using Geometric Features: A Review", Canadian Journal on Image Processing and Computer Vision Vol. 3, No. 1.
Index Terms
Keywords