Browse > Article
http://dx.doi.org/10.9708/jksci.2011.16.6.089

Implementation of augmented reality and object tracking using multiple camera  

Kim, Hag-Hee (Dept. of Computer Engineering, Korea University of Technology and Education)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.6, 2011 , pp. 89-97 More about this Journal
Abstract
When examining current process of object tracking and search, objects were tracked by extracting them from image that was inputted through fixed single camera and objects were recognized through Zoom function to know detailed information on objects tracked. This study proposed system that expresses information on area that can seek and recognize object tracked as augmented reality by recognizing and seeking object by using multi camera. The result of experiment on proposed system showed that the number of pixels that was included in calculation was remarkably reduced and recognition rate of object was enhanced and time that took to identify information was shortened. Compared with existing methods, this system has advantage of better accuracy that can detect the motion of object and advantage of shortening time that took to detect motion.
Keywords
Object Tracking; Multiple camera; Controller design; Augmented Reality; Marker;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Don Murray and Anup Basu: Motion tracking with an active camera. IEEE transactions on pattern analysis and machine intelligence, vol. 16, no. 5, (1994) pp.449-459   DOI   ScienceOn
2 Shoichi Araki, Takashi Matsuoka, Naokazu Yokoya and Haruo Takemura: Real time tracking of multiple moving object contrours in a moving camera image sequence. IEICE TRANS. INF. & SYST., vol. E83-D, No. 7, (2000) pp. 1583-1591
3 Arindam Biswas, Prithwijit Guha, Amitabha Mukerjee, K.S. Venkatesh: Intrusion detection and tracking with pan-tilt cameras. IET International Conference, (2006) pp. 565-571
4 Tamer Inanc, Mario Sznaier and Octavia Camps: Robust identification and model (in)validation of active-vision systems. Identification and control, ${\copyright}$ Copyright, Springer London, (2007), pp.167-200
5 C. Brown and D. Coombs : Real-time binocular smooth pursuit tracking. International Journal of Computer Vision. Vol. 11, no.2, (1993), pp.147-164   DOI   ScienceOn
6 L. Gu and J. Su : Gaze control on humanoid robot head. IEEE World Congress on Intelligent Control and Automation, pp.9144-9148
7 Y. C. Chen, L. W. Chang, and C. T. Hsu: Feature-based object tracking with an active camera, PCM2002, LNCS2532, (2002) pp.1137-1144
8 Mutsumi Watanabe, Nobuyuki Takeda, and Kazunori Onoguchi: A moving object recognition method by optical flow analysis. Proceedings of ICPR, 1051-4651/96, (1996) pp.528-533
9 L. Jordao, M. Perrone, J. P. Costeira, J. Santos-Victor: Active face and feature tracking. Image Analysis and Processing 1999, (1999) pp. 572-576
10 I. D. Reid and D. W. Murray : Active tracking of foveated feature clusters using affine structure. International Journal of Computer Vision, vol. 18, no. 1, 1996
11 Petros Maragos: Morphological filtering for image enhancement and feature detection. The image and Video Processing Handbook, 2nd edition, (2004) pp.135-156
12 NVIDIA CUDA Compute unified device architecture November - programming guide. ${\copyright}$ Copyright, NVIDIA Corporation (2007)
13 Rita Cucchiara, Andrea Prati, and Roberto Vezzani: Advanced video surveillance with pan tilt zoom cameras. Proc. of Workshop on Visual Surveillance (VS) at ECCV 2006, May (2006)
14 Peter I. Corke and Malcolm C. Good: Dynamic effects in visual closed-loop systems. IEEE Transactions on Robotics and Automation, vol. 12, no. 5, October (1996), pp. 671-683   DOI   ScienceOn