Age Estimation and its Progression from Face Images
Neha Sharma1, Reecha Sharma2, Neeru Jindal3

1Neha Sharma (UCOe, Punjabi University, Patiala, India),
2Reecha Sharma UCOe, Punjabi University, Patiala, India.
3Neeru Jindal T.I.E.T, Patiala, India. 

Manuscript received on 5 August 2019. | Revised Manuscript received on 11 August 2019. | Manuscript published on 30 September 2019. | PP: 2351-2355 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4414098319/2019©BEIESP | DOI: 10.35940/ijrte.C4414.098319
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Abstract: Face model improves the performance of evaluating the accurate age estimation with facial images and has enormous real-world applications. Human aging is a process of growing gradually old and mature. However, it is slow, depends upon person to person and most important it is irreversible. This paper mainly focuses on the various face model techniques, their performance metrics, databases, age estimation challenges to provide the researcher a great knowledge with recent journals in this field. Age estimation process progress with two modules: first part is feature extraction from the image and second module is age estimation. The accuracy or the desired output from age estimation model largely depends upon the features extraction, which if selected appropriately helps to achieve better results for research work.
Keywords: Age Estimation, Feature Extraction, Performance Metrics.

Scope of the Article:
High Performance Computing