Face image synthesis with weight and age progression using conditional adversarial autoencoder
The appearance of a human face changes with the change in body weight and age. With varying lifestyle choices, it is hard to imagine the appearance of a given human face in years to come. Future self-perception is highly associated with one's emotional state, as well as health behavior. Negativ...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
Springer London Ltd
2020
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/36774/ |
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| Summary: | The appearance of a human face changes with the change in body weight and age. With varying lifestyle choices, it is hard to imagine the appearance of a given human face in years to come. Future self-perception is highly associated with one's emotional state, as well as health behavior. Negative future self-perception can cause negative lifestyle choice and negative health behavior, leading to depression and eating disorder. In this paper, a new methodology is introduced for future self-face image synthesis using age and weight, resulting in visualization of future face image derived from given weight category and age. A Constrained Local Model is first used for weight progressed future face image synthesized and then age-progressed future face image is generated using Conditional Adversarial Auto Encoder. In the final step, both weight progressed and age-progressed face images fed to face morphing module which synthesized future face image by keeping natural looks. Experimental results show the advantages of proposed method with promising results. |
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