Browse > Article
http://dx.doi.org/10.9717/kmms.2018.21.8.876

Design and Implementation of a Stage Object Location Tracking Method using Texture Feature and CAMShift Algorithm  

Shin, Jung-Ah (Dept. of Computer Engineering, Dongseo University)
Kim, Do-Hee (Dept. of Computer Engineering, Dongseo University)
Hong, Seok-Keun (Industry Academy Cooperation Foundation, Dongseo University)
Cho, Dae-Soo (Dept. of Computer Engineering, Dongseo University)
Publication Information
Journal of Korea Multimedia Society / v.21, no.8, 2018 , pp. 876-887 More about this Journal
Abstract
In this paper, we propose an robust CAMShift method to track stage objects with a camera. In order to solve the problem of tracking object misdetection in existing CAMShift technique, MBR region is detected to separate the background and the subject, and the subject size of the region of interest is calculated to solve the problem of erroneously detecting a large region having a similar color distribution ratio. Also, by applying the color corelogram and MB-LBP to the part that can not be solved by the color ratio and the size limitation, accurate texture tracking is enabled by reflecting the texture characteristics. Experimental results show that the proposed method has good tracking performance for objects that do not deviate from the size of the subject set in the area of interest and accurately extracts the texture characteristics of different subjects with similar color distribution ratios.
Keywords
MBR; MB-LBP; Texture Feature; CAMShift; Color Correlogram;
Citations & Related Records
연도 인용수 순위
  • Reference
1 D.G. Kim, S.J. Lee, Y.M. Ahn, and D.H. Kim, "Development of Dynamic Object Location Tracking System for Using Ultra Wide Band Sensor - Mainly Applied to the Stage Technology by Immersive Media," Proceeding of 2015 Korean Society of Broadcast Engineers Summer Conference, pp. 125-128, 2015.
2 L. Lan, X. Wang, S. Zhang, D. Tao, W. Gao, and T. Huang, "Interacting Tracklets for Multi-Object Tracking," IEEE Transactions on Image Processing, Vol. 27, pp. 4585-4597, 2018.   DOI
3 P. Chen, H. Krim, and O. Mendoza, "A Theory of Phase Singularities for Image Representation and its Applications to Object Tracking and Image Matching," IEEE Transactions on Image Processing, Vol. 19, pp. 1706-1719, 2010.   DOI
4 S. Afef and J.Y. Ameni, "Object Tracking System Using Camshift Mean-shift and Kalman filter," World Academy of Science Engineering and Technology International Journal of Electronics and Communication Engineering, Vol. 6, No. 64, pp. 421-426, 2012.
5 C. Hsia, Y. Liou, and J. Chiang, "Directional Prediction CamShfit Algorithm Based on Adaptive Search Pattern For Moving Object Tracking," Journal of Real-Time Image Processing, Vol. 12, pp. 183-195, 2016.   DOI
6 S.J. Lee and M.C. Won, "A Vision Based People Tracking and Following for Mobile Robots Using CAMSHIFT and KLT Feature Tracker," Journal of Korea Multimedia Society, Vol. 17, No. 7, pp. 787-796, 2014.   DOI
7 R.C. Gonzalez and R.E. Woods, Digital Image Processing (Third Edition), Pearson Education, Upper Saddle River, New Jersey, 2011.
8 D. Soni and K. J. Mathai, "An Efficient Content Based Image Retrieval System Based on Color Space Approach Using Color Histogram and Color Correlogram," Proceeding of 2015 Fifth International Conference on Communication Systems and Network Technologiess, pp. 488-492, 2015.
9 T. Ojala, M. Pietikainen, and T. Meanpaa, "Multiresolution Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 3, pp. 971-987, 2002.   DOI
10 T. Ojala, M. Pietikainen, and D. Harwood, "A Comparative Study of Texture Measures with Classification Based on Feature Distributions," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29, pp. 51-59, 1996.
11 T. Liu, F. Li, and R. Wang, "Human Face Gender Identification System Based on MBLBP," Chinese Control and Decision, pp. 1721-1725, 2018.
12 T. Zhang, H. Hu, and B. Li, "A Naturalness Preserved Fast Dehazing Algorithm Using HSV Color Space," IEEE Access, Vol. 6, pp. 10644-10649, 2018.   DOI
13 D. Soni and K.J. Mathai, "An Efficient Content Based Image Retrieval System Based on Color Space Approach Using Color Histogram and Color Correlogram," Proceeding of 2015 Fifth International Conference on Communication Systems and Network Technologies, pp. 488-492, 2015.