Technical Challenges, Performance Metrics and Advancements in Face Recognition System

Harakannanavar, Sunil S.; Prashanth, C. R.; Kanabur, Vidyashree; Puranikmath, Veena I; Raja, K. B.

doi:10.26438/ijcse/v7i3.836847

Cited by 6 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This includes technical enhancements for privacy-by-design and legislative efforts to protect individuals' rights. Research into privacy-preserving technologies such as federated learning, where data can be processed locally without being sent to a central server, will be increasingly vital (Kanabur et al, 2019;Schroff et al, 2015) . Cross-Disciplinary Approaches.…”

Section: Challenges and Limitationsmentioning

confidence: 99%

Review of Challenges and Innovations in Occluded Facial Recognition in Disguise and Crowd

Singh,

Sirohi

et al. 2024

IJRASET

View full text Add to dashboard Cite

Facial recognition technology is critical in modern security and identification systems, yet it faces significant challenges when dealing with occluded faces, whether due to disguises or in crowds. This review explores the complexities of occluded facial recognition, highlighting the obstacles presented by partial or complete obstruction of facial features by various elements like clothing, accessories, or other people in crowded spaces. These occlusions, intentional or otherwise, complicate the identification process, rendering traditional recognition systems less effective. Recent advancements in machine learning, particularly through Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs), have ushered in innovative solutions that enhance the system's ability to recognize faces even when significant portions are obscured. These developments signify a move towards more adaptable and precise occluded facial recognition technologies, essential for real-world applications where occlusions are unpredictable. The paper discusses ongoing challenges and innovations considerations, various occluded system performance metrics and conclude with way ahead for Researchers and Practioners

show abstract

Section: Challenges and Limitationsmentioning

confidence: 99%

Review of Challenges and Innovations in Occluded Facial Recognition in Disguise and Crowd

Singh,

Sirohi

et al. 2024

IJRASET

View full text Add to dashboard Cite

show abstract

“…One of the most distinguished biometric attributes is facial features, which are the most compatible with Machine Readable Travel Documents [1]. The advantage of facial features is that they can be captured at a distance without permission.…”

Section: Introductionmentioning

confidence: 99%

Deeply Learned Invariant Features for Component-based Facial Recognition

Hassan¹,

Viriri²

2022

IJACSA

View full text Add to dashboard Cite

Face recognition underage variation is a challenging problem. It is a difficult task because ageing is an intrinsic variation, not like pose and illumination, which can be controlled. We propose an approach to extract invariant features to improve facial recognition using facial components. Can facial recognition over age progression be improved by resizing independently each individual facial component? The individual facial components: eyes, mouth, and nose were extracted using the Viola-Jones algorithm. Then we utilize the eyes region rectangle with upper coordinates to detect the forehead and lower coordinates with the nose rectangle to detect the cheeks. The proposed work uses Convolutional Neural Network with an ideal input image size for each facial component according to many experiments. We sum up component scores by applying weighted fusion for a final decision. The experiments prove that the nose component provides the highest score contribution among other ones, and the cheeks are the lowest. The experiments were conducted on two different facial databases-MORPH, and FG-NET databases. The proposed work achieves a state-of-the-art accuracy that reaches 100% on the FG-NET dataset and the results obtained on the MORPH dataset outperform the accuracy results of the related works in the literature.

show abstract