Mean LBP and modified fuzzy C-means weighted hybrid feature for illumination invariant mean-shift tracking

@article{Phadke2017MeanLA,
  title={Mean LBP and modified fuzzy C-means weighted hybrid feature for illumination invariant mean-shift tracking},
  author={Gargi Phadke and Rajbabu Velmurugan},
  journal={Signal, Image and Video Processing},
  year={2017},
  volume={11},
  pages={665-672}
}
Object tracking is a critical task in surveillance and activity analysis. Two main issues for tracking are appearance (illumination) and structural (size of a target) variations of the object. We propose a method which is robust and addresses these issues by incorporating features that are less variant to these changes. The proposed features are mean local binary pattern (mLBP), an illumination invariant texture feature, and modified fuzzy c-means (MFCM) weighted color histogram to handle both… Expand
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