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A survey of genetic algorithm-based face recognition

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Abstract

Traditionally, special objects can be detected and recognized by the template matching method, but the recognition speed has always been a problem. In addition, for recognition by a neural network, training the data is always time-consuming. In this article, the current method of genetic algorithm-based face recognition is summarized, and experiments for real-time use are described. The chromosomes generated by the genetic algorithm (GA) contain information (parameters) about the face, and genetic operators are used to detect and obtain the position of the face of interest in an image. Here, the parameters of the coordinates (x, y) of the center of the face, the rate of scale, and the angle of rotation θ, are encoded into the GA.

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Author information

Authors and Affiliations

  1. College of Electronic Information and Automation, Tianjin University of Science and Technology, No. 1038 Dagu Nanlu, Hexi District, Tianjin, 300222, PR China

    Fengzhi Dai

  2. Department of Electronic Mechanical Engineering, Oshima National College of Maritime Technology, Oshima, Japan

    Naoki Kushida

  3. Vestas Wind Technology (China) Co., Beijing, China

    Liqiang Shang

  4. ALife Robotics Co., Nippon Bunri University, Oita, Japan

    Masanori Sugisaka

Authors
  1. Fengzhi Dai
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  2. Naoki Kushida
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  3. Liqiang Shang
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  4. Masanori Sugisaka
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Corresponding author

Correspondence to Naoki Kushida.

Additional information

This work was presented in part at the 16th International Symposium on Artifi cial Life and Robotics, Oita, Japan, January 27–29, 2011

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Cite this article

Dai, F., Kushida, N., Shang, L. et al. A survey of genetic algorithm-based face recognition. Artif Life Robotics 16, 271–274 (2011). https://doi.org/10.1007/s10015-011-0941-9

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  • DOI: https://doi.org/10.1007/s10015-011-0941-9

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