Int. J. of Business Intelligence and Data Mining   »   2018 Vol.13, No.1/2/3

 

 

Title: Multiple object tracking by employing shaped-based features and Kalman filter

 

Authors: Felix M. Philip; Rajeswari Mukesh

 

Addresses:
Department of Electronics and Communication Engineering, Hindustan University, Chennai, India
Department of Computer Science and Engineering, Hindustan University, Chennai, India

 

Abstract: There has been fast development happening in the multimedia and the related technologies, particularly associated with visual tracking and search operations. Moving target detection has been comprehensively engaged in various arenas but has the disadvantage that the scheme is frequently complex and also that tracking is affected numerous external factors. In this article, multiple objects recognition and tracking is projected so as to progress the method and make it more robust and general with assistance of shape-based features and Kalman filter. Primarily, the input video is rehabilitated to frames and then manually segmented for object segmentation. Consequently, the objects are tracked with the help of Kalman filtering. The method is assessed under standard evaluation metrics of error value and the score value. The technique achieved maximum score values of 95% and minimum error value of 25%. The results validate the effectiveness of the technique.

 

Keywords: moving object detection; tracking; shape-based features; Kalman filtering and segmentation.

 

DOI: 10.1504/IJBIDM.2017.10005166

 

Int. J. of Business Intelligence and Data Mining, 2018 Vol.13, No.1/2/3, pp.331 - 346

 

Available online: 03 Nov 2017

 

 

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