Feature extraction system for age estimation

Hironobu Fukai; Hironori Takimoto; Yasue Mitsukura; Minoru Fukumi

doi:10.1007/978-3-540-85565-1_57

Feature extraction system for age estimation

Hironobu Fukai, Hironori Takimoto, Yasue Mitsukura, Minoru Fukumi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we propose the novel age estimation system with the real-coded genetic algorithm (RGA) and the neural network (NN). The age is one of important information in our living. There are a lot of studies on age estimation by the computer. However, the conventional method of the age estimation, the most of them are the studies intended for an actual age. Therefore, we pay attention to the mechanism of human age perception. The apparent age feature is extracted by the fourier transform, and the important spectrum for the age perception are selected by the RGA. The age is estimated by the 3 layered NN. It is considered that it can extract important age feature using the RGA and it can analyze the important feature area. In addition, proposed method extracts the age feature at each age. In order to show the effectiveness of the proposed method, we show the simulation examples. From the simulation results, we can confirm that the proposed method works well.

Original language	English
Title of host publication	Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings
Publisher	Springer Verlag
Pages	458-465
Number of pages	8
Edition	PART 2
ISBN (Print)	3540855645, 9783540855644
DOIs	https://doi.org/10.1007/978-3-540-85565-1_57
Publication status	Published - 2008
Externally published	Yes
Event	12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008 - Zagreb, Croatia Duration: 2008 Sept 3 → 2008 Sept 5

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	5178 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
Country/Territory	Croatia
City	Zagreb
Period	08/9/3 → 08/9/5

Keywords

Age estimation
Neural network (NN)
Real-coded genetic algorithm(RGA)

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-85565-1_57

Cite this

Fukai, H., Takimoto, H., Mitsukura, Y., & Fukumi, M. (2008). Feature extraction system for age estimation. In Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings (PART 2 ed., pp. 458-465). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5178 LNAI, No. PART 2). Springer Verlag. https://doi.org/10.1007/978-3-540-85565-1_57

Feature extraction system for age estimation. / Fukai, Hironobu; Takimoto, Hironori; Mitsukura, Yasue et al.

Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings. PART 2. ed. Springer Verlag, 2008. p. 458-465 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5178 LNAI, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Fukai, H, Takimoto, H, Mitsukura, Y & Fukumi, M 2008, Feature extraction system for age estimation. in Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5178 LNAI, Springer Verlag, pp. 458-465, 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008, Zagreb, Croatia, 08/9/3. https://doi.org/10.1007/978-3-540-85565-1_57

Fukai H, Takimoto H, Mitsukura Y, Fukumi M. Feature extraction system for age estimation. In Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings. PART 2 ed. Springer Verlag. 2008. p. 458-465. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-540-85565-1_57

Fukai, Hironobu ; Takimoto, Hironori ; Mitsukura, Yasue et al. / Feature extraction system for age estimation. Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings. PART 2. ed. Springer Verlag, 2008. pp. 458-465 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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AU - Fukai, Hironobu

AU - Takimoto, Hironori

AU - Mitsukura, Yasue

AU - Fukumi, Minoru

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N2 - In this paper, we propose the novel age estimation system with the real-coded genetic algorithm (RGA) and the neural network (NN). The age is one of important information in our living. There are a lot of studies on age estimation by the computer. However, the conventional method of the age estimation, the most of them are the studies intended for an actual age. Therefore, we pay attention to the mechanism of human age perception. The apparent age feature is extracted by the fourier transform, and the important spectrum for the age perception are selected by the RGA. The age is estimated by the 3 layered NN. It is considered that it can extract important age feature using the RGA and it can analyze the important feature area. In addition, proposed method extracts the age feature at each age. In order to show the effectiveness of the proposed method, we show the simulation examples. From the simulation results, we can confirm that the proposed method works well.

AB - In this paper, we propose the novel age estimation system with the real-coded genetic algorithm (RGA) and the neural network (NN). The age is one of important information in our living. There are a lot of studies on age estimation by the computer. However, the conventional method of the age estimation, the most of them are the studies intended for an actual age. Therefore, we pay attention to the mechanism of human age perception. The apparent age feature is extracted by the fourier transform, and the important spectrum for the age perception are selected by the RGA. The age is estimated by the 3 layered NN. It is considered that it can extract important age feature using the RGA and it can analyze the important feature area. In addition, proposed method extracts the age feature at each age. In order to show the effectiveness of the proposed method, we show the simulation examples. From the simulation results, we can confirm that the proposed method works well.

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KW - Real-coded genetic algorithm(RGA)

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ER -

Feature extraction system for age estimation

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Keywords

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