Abstract
In real time moving object tracking, various unconstraint factors such as severe occlusion and background clutter remain a challenge for developing an effective yet robust tracking method. In this study, a novel moving object tracking algorithm based on the modified flower pollination algorithm (MFPA) is proposed. A search window with the features of centroid coordinates and width of the search window is used to locate the position of the moving object. The sub-image within the search window is then extracted. The hue, saturation and value (HSV) histogram of the extracted region is calculated in order to model the object appearance representation. Subsequently, the Bhattacharyya distance between the HSV histograms from two consecutive frames is formulated as the fitness function of MFPA, in which maximizing the similarity of both histograms is sought after. The comparative experimental results show that the developed algorithm outperforms others in terms of efficiency and accuracy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
