NDLI: Face recognition across age progression

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Face recognition across age progression

Content Provider	Indraprastha Institute of Information Technology, Delhi
Author	Yadav, Daksha
Abstract	The phenomenon of “aging” in humans leads to significant variations in facial features. Various factors such as bone growth, ethnicity, and dietary habits influence the facial aging pattern. This increases the difficulty in performing automated face recognition. The contribution of this research is two fold. Firstly, an algorithm is developed that improves the performance of face recognition by applying the bacteria foraging fusion algorithm. The proposed algorithm mitigates the effect of facial changes caused due to aging by combining the LBP features of global and local facial regions at match score level, by means of the bacteria foraging fusion algorithm. Experimental results are presented using the FG-Net and IIITDelhi facial aging databases. The IIITDelhi facial aging database, collected by the us, consists of over 2600+ age-separated labeled face images of 102 individuals. To account for real life and natural conditions, images include changes in the face due to illumination, pose, and presence of accessories such as eyeglasses. The results demonstrate that the proposed approach outperforms traditional fusion schemes, existing algorithms and a commercial system. The second fold contribution is conducting a cognitive study to understand how humans perceive facial age. Facial cues that are utilized by humans for precisely estimating the age of people belonging to various age groups are investigated. Different facial region images are used to evaluate which facial cues are used by humans in recognizing the individual given his age-separated images. The findings of this research encouraged us to employ them into automatic face recognition algorithm which resulted in obtaining improved performance. The results have been presented on IIIT Delhi facial aging and MORPH databases.
File Format	PDF
Language	English
Access Restriction	Authorized
Subject Keyword	Facial Aging Face Recognition Bacterial Foraging Age Estimation Perception based Study
Content Type	Text
Educational Degree	Bachelor of Technology (B.Tech.)
Resource Type	Thesis
Subject	Data processing & computer science

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