Abstract:
This study presents an age and gender estimation system that considers ethnic difference in face images using a Convolutional Neural Network(CNN) and Support Vector Machi...Show MoreMetadata
Abstract:
This study presents an age and gender estimation system that considers ethnic difference in face images using a Convolutional Neural Network(CNN) and Support Vector Machine(SVM). Most age and gender estimation systems using face images are trained on ethnicity-biased databases. Therefore, these systems show limited performance on face images of ethnic groups occupying a small proportion of the training data. To resolve this problem, we propose an age and gender estimation system that considers the ethnic difference in face images. At the first stage of the system, the ethnicity of the facial image is determined by a CNN trained with manually collected face images of Asian and non-Asian celebrities. Then, one of the SVM classifiers is selected according to the ethnicity for the final age and gender estimation. We compared the proposed system with an estimation system that does not consider ethnic difference. The result shows improved performance for age estimation but no improvement for gender recognition.
Published in: 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)
Date of Conference: 28 August 2017 - 01 September 2017
Date Added to IEEE Xplore: 14 December 2017
ISBN Information:
Electronic ISSN: 1944-9437
Citations are not available for this document.
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Cites in Papers - IEEE (5)
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1.
Deepika Verma, Kamal Dhanda, Munish Kumar, Monali Gulhane, "Facial Recognition Unlocking Potential Facing Challenges in Face and Gender Identification", 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE), pp.125-130, 2024.
2.
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4.
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5.
Ritwika Gautam, Poorva Mahara, "Perceptive advertising using standardised facial features", 2019 International Conference on Digitization (ICD), pp.1-7, 2019.
Cites in Papers - Other Publishers (5)
1.
Bilal Hassan, Ebroul Izquierdo, Krishna Chandramouli, "Performance Assessment of Soft Biometrics Technologies for Border Crossing" in Security Technologies and Social Implications, pp.82-121, 2023.
2.
Muhammad Hameed Siddiqi, Khalil Khan, Rehan Ullah Khan, Amjad Alsirhani, "Face Image Analysis Using Machine Learning: A Survey on Recent Trends and Applications", Electronics, vol.11, no.8, pp.1210, 2022.
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