Volume 12 Number 5 (May. 2017)
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JSW 2017 Vol.12(5): 326-338 ISSN: 1796-217X
doi: 10.17706/jsw.12.5.326-338

A Robust Framework for Accurate Face Tracking

Ali Ahmed
IT Department, Faculty of Computers and Information, Menoufia University, Shebin El-kom, Egypt

Abstract—Face detection and tracking are of the most challenging problems of the object tracking field because of the large variability of faces and facial expressions. In this paper, two different algorithms for face tracking based on unscented Kalman filter (UKF) are proposed. The first proposed algorithm is UKF based on Viola-Jones algorithm. Viola-Jones is extremely fast feature computation, efficient feature selection, and scale and location invariant detector. The second proposed algorithm is UKF based on mean shift using the corrected background weighted histogram (CBWH) scheme. This scheme can effectively reduce background's interference in target localization and consequently can guarantee accurate localization of the target. The tracking step is completed using UKF that can estimate the next state with a high level of accuracy. So the two proposed algorithms are used to enhance the solution of face tracking problems. The performance of the two different proposed algorithms is evaluated with other well-known face tracking algorithms.

Index Terms—Mean shift, corrected background weighted histogram, unscented kalman filter, Camshift.

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Cite: Ali Ahmed, "A Robust Framework for Accurate Face Tracking," Journal of Software vol. 12, no. 5, pp. 326-338, 2017.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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