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Directional Age-Primitive Pattern (DAPP) for Human Age Group Recognition and Age Estimation

Author Affiliations
Kyung Hee University, University of Dhaka, King Saud University
Published InIEEE Transactions on Information Forensics and Security
Year2017
Citations40

Abstract

An appropriate aging description from face image is the prime influential factor in human age recognition, but still there is an absence of a specially engineered aging descriptor, which can characterize discernible facial aging cues (e.g., craniofacial growth, skin aging) from a detailed and more finer point of view. To address this issue, we propose a local face descriptor, directional age-primitive pattern (DAPP), which inherits discernible aging cue information and is functionally more robust and discriminative than existing local descriptors. We introduce three attributes for coding the DAPP description. First, we introduce Age-Primitives encoding aging related to the most crucial texture primitives, yielding a reasonable and clear aging definition. Second, we introduce an encoding concept dubbed as Latent Secondary Direction,…
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