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DOI: 10.14569/IJACSA.2010.010622
PDF

A Face Replacement System Based on Face Pose Estimation

Author 1: Kuo Yu Chiu
Author 2: Shih-Che Chien
Author 3: Sheng-Fuu Lin

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 1 Issue 6, 2010.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Face replacement system plays an important role in the entertainment industries. However, most of these systems nowadays are assisted by hand and specific tools. In this paper, a new face replacement system for automatically replacing a face with image processing technique is described. The system is divided into two main parts: facial feature extraction and face pose estimation. In the first part, the face region is determined and the facial features are extracted and located. Eyes, mouth, and chin curve are extracted by their statistical and geometrical properties. These facial features are used as the information for the second part. A neural network is adopted here to classify the face pose according to the feature vectors which are obtained from the different ratio of facial features. From the experiments and some comparisons, they show that this system works better while dealing with different pose, especially for non-frontal face pose.

Keywords: Facial feature, Face replacement, Neural network, Support vector machine (SVM)

Kuo Yu Chiu, Shih-Che Chien and Sheng-Fuu Lin. “A Face Replacement System Based on Face Pose Estimation ”. International Journal of Advanced Computer Science and Applications (IJACSA) 1.6 (2010). http://dx.doi.org/10.14569/IJACSA.2010.010622

@article{Chiu2010,
title = {A Face Replacement System Based on Face Pose Estimation },
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2010.010622},
url = {http://dx.doi.org/10.14569/IJACSA.2010.010622},
year = {2010},
publisher = {The Science and Information Organization},
volume = {1},
number = {6},
author = {Kuo Yu Chiu and Shih-Che Chien and Sheng-Fuu Lin}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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