A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.

Original languageEnglish
Article number879031
JournalScientific World Journal
Volume2014
DOIs
Publication statusPublished - 2014

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Bees
bee
Face recognition
Adaptive algorithms
Datasets
Facial Recognition
modeling
experiment
Experiments

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Environmental Science(all)
  • Medicine(all)

Cite this

A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony. / Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Ali Othman, Zulaiha.

In: Scientific World Journal, Vol. 2014, 879031, 2014.

Research output: Contribution to journalArticle

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