Face Recognition: Issues, Methods and Alternative Applications

Abstract

Face recognition, as one of the most successful applications of image analysis, has recently gained significant attention. It is due to availability of feasible technologies, including mobile solutions. Research in automatic face recognition has been conducted since the s, but the problem is still largely unsolved. Last decade has provided significant progress in this area owing to advances in face modelling and analysis techniques. Although systems have been developed for face detection and tracking, reliable face recognition still offers a great challenge to computer vision and pattern recognition researchers. There are several reasons for recent increased interest in face recognition, including rising public concern for security, the need for identity verification in the digital world, face analysis and modelling techniques in multimedia data management and computer entertainment. In this chapter, we have discussed face recognition processing, including major components such as face detection, tracking, alignment and feature extraction, and it points out the technical challenges of building a face recognition system. We focus on the importance of the most successful solutions available so far. The final part of the chapter describes chosen face recognition methods and applications and their potential use in areas not related to face recognition.

LoRa System for Monitoring and Facial Recognition

“…The training process in these algorithms is, on average, considerably slower than the previous techniques as it needs a much higher number of training steps. However, the results obtained almost always outclass the other options in terms of precision and accuracy, thus, outweighing its negative aspects [37]- [40].…”

Penguatan Ketepatan Pengenalan Wajah Viola-Jones Dengan Pelacakan

“…31 dikembangkan karena adanya kajian tentang ketepatan dalam pengenalan wajah. Banyak literatur menyebutkan ketepatan pengenalan wajah merupakan studi yang rumit karena wajah memiliki tingkat kompleksitas yang tinggi [18][19][20][21][22][23]. Fitur wajah setiap orang sangat bervariasi dan berubah dari waktu ke waktu, baik karena umur yang menua maupun perubahan ekspresi, bahkan perubahan bisa berlangsung dalam waktu singkat [24].…”

Smart Face Detection and Recognition in Low Resolution Images Using Alexnet CNN Compare Accuracy with SVM

“…Face Recognition has become an important research field for over a couple of decades and several face recognition systems have been developed (Wójcik, Gromaszek, and Junisbekov 2016). Though fingerprint identification is an unique method, it is not feasible for classifying humans with respect to gender, color creed etc., for further analysis (Ramkumar and Logashanmugam 2018).…”

“…It is mainly used for personnel identification (Ramkumar and Logashanmugam 2016). It has many applications in our day to day life like surveillance cameras installation for monitoring person in workplaces, temples, buildings, border security, marketing, smart gadgets, biometric systems etc (Wójcik, Gromaszek, and Junisbekov 2016;Rai et al 2019). object at the same time and measuring their accuracy on a single dataset of faces.…”