Reference Hub2
Deep Appearance Model and Crow-Sine Cosine Algorithm-Based Deep Belief Network for Age Estimation

Deep Appearance Model and Crow-Sine Cosine Algorithm-Based Deep Belief Network for Age Estimation

Anjali A. Shejul, Kinage K. S., Eswara Reddy B.
Copyright: © 2021 |Volume: 12 |Issue: 3 |Pages: 23
ISSN: 1941-6237|EISSN: 1941-6245|EISBN13: 9781799860280|DOI: 10.4018/IJACI.2021070109
Cite Article Cite Article

MLA

Shejul, Anjali A., et al. "Deep Appearance Model and Crow-Sine Cosine Algorithm-Based Deep Belief Network for Age Estimation." IJACI vol.12, no.3 2021: pp.185-207. http://doi.org/10.4018/IJACI.2021070109

APA

Shejul, A. A., K. S., K., & B., E. R. (2021). Deep Appearance Model and Crow-Sine Cosine Algorithm-Based Deep Belief Network for Age Estimation. International Journal of Ambient Computing and Intelligence (IJACI), 12(3), 185-207. http://doi.org/10.4018/IJACI.2021070109

Chicago

Shejul, Anjali A., Kinage K. S., and Eswara Reddy B. "Deep Appearance Model and Crow-Sine Cosine Algorithm-Based Deep Belief Network for Age Estimation," International Journal of Ambient Computing and Intelligence (IJACI) 12, no.3: 185-207. http://doi.org/10.4018/IJACI.2021070109

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Age estimation has been paid great attention in the field of intelligent surveillance, face recognition, biometrics, etc. In contrast to other facial variations, aging variation presents several unique characteristics, which make age estimation very challenging. The overall process of age estimation is performed using three important steps. In the first step, the pre-processing is performed from the input image based on Viola-Jones algorithm to detect the face region. In the second step, feature extraction is done based on three important features such as local transform directional pattern (LTDP), active appearance model (AAM), and the new feature, deep appearance model (Deep AM). After feature extraction, the classification is carried out based on the extracted features using deep belief network (DBN), where the DBN classifier is trained optimally using the proposed learning algorithm named as crow-sine cosine algorithm (CS).

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.