Open AccessNovel Adaptive Background Segmentation Algorithm for Multiple Object Tracking
Author(s) -
V Ramalakshmi @ Kanthimathi,
M. Germanus Alex
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.27.17984
Subject(s) - computer science , computer vision , artificial intelligence , video tracking , segmentation , tracking (education) , object (grammar) , sequence (biology) , mean shift , market segmentation , pattern recognition (psychology) , psychology , pedagogy , marketing , biology , business , genetics
Multiple object tracking plays a vital role in many applications. The objective of this paper is to track multiple objects in all the scenes of the video sequence. In this paper, an algorithm is proposed to identify objects between scenes by dividing the scenes in the video sequence. Within each scene, objects are identified and tracked between scenes by segmenting the background adaptively. The proposed method is tested on four publicly available datasets. The experimental results substantially proved that the proposed method achieves better performance than other recent methods.