A survey of genetic algorithm-based face recognition
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-b...
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| Veröffentlicht in: | Artificial life and robotics 2011-09, Vol.16 (2), p.271-274 |
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| container_title | Artificial life and robotics |
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| creator | Dai, Fengzhi Kushida, Naoki Shang, Liqiang Sugisaka, Masanori |
| description | 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. |
| doi_str_mv | 10.1007/s10015-011-0941-9 |
| format | Article |
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| source | Springer Nature - Complete Springer Journals |
| subjects | Algorithms Artificial Intelligence Computation by Abstract Devices Computer Science Control Face recognition Genetic algorithms Genetics Mechatronics Neural networks Object recognition Original Article Recognition Robotics |
| title | A survey of genetic algorithm-based face recognition |
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