Ta, D.N., Chen, W.C., Gelfand, N., et al. (2009) SURFTrack: Efficient Tracking and Continuous Object Recognition Using Local Features Descriptors. Computer Vision and Pattern Recognition (CVPR09), Miami, 2937-2943.

has been cited by the following article:

• TITLE: A Target Tracking Algorithm Based on Improved Camshift and UKF

  AUTHORS: Zouguo Yan, Weiguo Liang, Haidong lv

  KEYWORDS: Camshift, UKF, Tracking Algorithm, Sheltered Problem, Interference of the Background Color

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.7 No.13, December 18, 2014

  ABSTRACT: A tracking algorithm based on improved Camshift and UKF is proposed in this paper to deal with the problems which exist in traditional Camshift algorithm, such as artificial orientation and tracking failure under color interference as well as object’s changed illumination occlusion. Meanwhile, in order to solve the sheltered problem, the UKF is combined with improved Camshift algorithm to predict the position of the target effectively. Experiment results show that the proposed algorithm can avoid the interference of the background color and solve the sheltered problem of the object, so that achieving a precise and timely tracking of moving objects. Also it has better robustness to color noises and occlusion when the object’s scale changes and deformation occurs.