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Paper Title
Improved Human Opinion Dynamics Based Particle Filter Object Tracking For Videos
  Harmanjot Kaur,  Er. Inderjeet Singh

Object tracking is a technique that is being used from past centuries. In the surveillance system, several vision based methods are utilized for various objects. In the first part, a fast method is presented for background subtraction to handle various scene changes. The maximum likelihood estimation algorithm found within the above paragraph try to modify the objective functions. These approaches are still sensitive to initialization and other parameters like predicted position of the tracked object, occlusion time etc. The proposed method combines the background modeling and particle filter to track multiple objects. In the object tracking process the object is considered to be in motion if its location is changing with respect to its background. By using background subtraction method the change of frame is detected, in case if there is no difference between the two frames then the object is considered to be in a static position. The proposed work is to use human opinion dynamic algorithm for particle filter tuning in order to make the prediction more effective. As the proposed algorithm involved solving the minimization problem for each drawn sample with the proposed model, the proposed system has been planned for real-time applications. The results will be presented to verify the same.

Keywords- GSA, HOD, CODO, MLE
Publication Details
Unique Identification Number - IJEDR1702269
Page Number(s) - 1711-1716
Pubished in - Volume 5 | Issue 2 | June 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Harmanjot Kaur,  Er. Inderjeet Singh,   "Improved Human Opinion Dynamics Based Particle Filter Object Tracking For Videos", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 2, pp.1711-1716, June 2017, Available at :http://www.ijedr.org/papers/IJEDR1702269.pdf
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