International Journal of Contents

  • 제9권3호
  • /
  • Pages.9-14
  • /
  • 2013
  • /
  • 1738-6764(pISSN)
  • /
  • 2093-7504(eISSN)
한국콘텐츠학회 (The Korea Contents Association)
권호 표지
DOI QR코드

DOI QR Code

Scale Invariant Single Face Tracking Using Particle Filtering With Skin Color

  • Adhitama, Perdana (School of Electronics & Computer Engineering Chonnam National University) ;
  • Kim, Soo Hyung (School of Electronics & Computer Engineering Chonnam National University) ;
  • Na, In Seop (School of Electronics & Computer Engineering Chonnam National University)
  • 투고 : 2013.02.07
  • 심사 : 2013.08.22
  • 발행 : 2013.09.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In this paper, we will examine single face tracking algorithms with scaling function in a mobile device. Face detection and tracking either in PC or mobile device with scaling function is an unsolved problem. Standard single face tracking method with particle filter has a problem in tracking the objects where the object can move closer or farther from the camera. Therefore, we create an algorithm which can work in a mobile device and perform a scaling function. The key idea of our proposed method is to extract the average of skin color in face detection, then we compare the skin color distribution between the detected face and the tracking face. This method works well if the face position is located in front of the camera. However, this method will not work if the camera moves closer from the initial point of detection. Apart from our weakness of algorithm, we can improve the accuracy of tracking.

키워드

참고문헌

  1. Abullah Bulbul, Zeynep Cipilogu and Tolga Capin. "A Face Tracking Algorithm for User Interaction in Mobile Devices," Proc. International Conference on CyberWorlds, 2009, pp. 385-390.
  2. Arnaud Doucet and Adam M. Johansen, A Tutorial on Particle Filter and Smoothing: Fifteen years later, Oxford handbook of nonlinear filtering, Oxford, December, 2009, pp. 4-6.
  3. Der-Chun Chenrn, "Real Time Color Based Particle Filter for Object Tracking with Dual Cache Architecture, "Proc 8th IEEE International Conference on Advanced Video and Signal Based Surveillance," 2011, pp. 148-153.
  4. Gary R.Bradski, "Computer Vision Tracking For Use in a Perceptual Interface," 1998, Intel Technology Journal, vol. 2. p. 1015.
  5. Irshad Ali and Matthew N. Dailey, "Multiple Human Tracking in High-Density Crowds," Proc 11th International Conference ACIVS, Springer, 2012, pp. 540-549.
  6. K.Nummiaro, E.B. Koller-Meier and L Van Gool, "Object Tracking with An Adaptive Color Based Particle Filter," Proc. 24th DAGM Symposium on Pattern Recognition", Springer Berlin Heidelberg, 2002, pp. 353-360.
  7. M. Isard and A Blake, "Condensation: conditional density propagation for visual tracking," International Journal of Computer Vision, vol. 29(1), 1998, pp. 5-28. https://doi.org/10.1023/A:1008078328650
  8. Md.Zahidul Islam, Chi-Min Oh, Jun Sung Lee and Chil-Woo Lee, "Multi_part Histogram based visual tracking with Maximum of Posteriori," Proc. 2nd International Conference on Computer Engineering and Technology (ICCET), 2010, pp. 435-439.
  9. P.Perez, C Hue, J.Vermaak and M.Gangnet, "Color Based probabilistic tracking," Proc. 7th European Conference on Computer Vision-Part I, 2002, pp. 661-675.
  10. T.Kailath, "The Divergence and Bhattacharyya Distance Measures in Signal Selection," IEEE Transactions on Communication Technology, vol. 15(1), pp. 52-62.
  11. Zia Khan, Tucker Balch, and Frank Dellaert, "MCMCbased Particle Filter for Tracking a variable number of Interacting Targets," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27(11), pp. 1825-1819.
  12. Cian Wu, Lihong Li, Jianhuang LAU and Jian Huang, "A Framework of Face Tracking with Classification using CAMShift-C and LBP," Proc. 5th International Conference on Image and Graphics, 2009, pp. 217-222.
  13. M. Jones and P. Viola, "Fast and robust classification using asymmetric AdaBoost and a detector cascade," Proc. of NIPS, 2002.
  14. M. Jones and P. Viola, "Rapid object detection suing boosted cascade of simple features," Proc. of CVPR, 2001.
  15. G.Bradski, "Computer Vision Face Tracking for Use in a Perceptual user Interface," Proc. IEEE Workshop Applications of Computer Vision, 1998, pp. 214-219.