Advances in Facial Recognition

A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces, typically employed to authenticate users through ID verification services, works by pinpointing and measuring facial features from a given image.

Development began on similar systems in the 1960s, beginning as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics. Because computerized facial recognition involves the measurement of a human's physiological characteristics, facial recognition systems are categorized as biometrics. Although the accuracy of facial recognition systems as a biometric technology is lower than iris recognition and fingerprint recognition, it is widely adopted due to its contactless process. Facial recognition systems have been deployed in advanced human– computer interaction, video surveillance and automatic indexing of images.

Sample Chapter(s)
preface (51 KB)
Components of the Book:
  • Chapter 1
    Reading And Reacting To Faces, The Effect Of Facial Mimicry In Improving Facial Emotion Recognition In Individuals With Antisocial Behavior And Psychopathic Traits
  • Chapter 2
    The Aftereffect Of The Ensemble Average Of Facial Expressions On Subsequent Facial Expression Recognition
  • Chapter 3
    Imitation And Recognition Of Facial Emotions In Autism: A Computer Vision Approach
  • Chapter 4
    Facial Expression Recognition As A Candidate Marker For Autism Spectrum Disorder: How Frequent And Severe Are Deficits?
  • Chapter 5
    A Novel Facial Image Recognition Method Based On Perceptual Hash Using Quintet Triple Binary Pattern
  • Chapter 6
    Facial Emotion Recognition Impairment Predicts Social And Emotional Problems In Children With (Subthreshold) Adhd
  • Chapter 7
    Facial Emotion Recognition In Adopted Children
  • Chapter 8
    Generalisation And Robustness Investigation For Facial And Speech Emotion Recognition Using Bio-Inspired Spiking Neural Networks
  • Chapter 9
    Relative Judgment Theory And The Mediation Of Facial Recognition: Implications For Theories Of Eyewitness Identification
  • Chapter 10
    A Fuzzy Logic Approach To Reliable Real-Time Recognition Of Facial Emotions
  • Chapter 11
    Personalized Models For Facial Emotion Recognition Through Transfer Learning
  • Chapter 12
    Differences Between Autistic And Non‑Autistic Adults In The Recognition Of Anger From Facial Motion Remain After Controlling For Alexithymia
  • Chapter 13
    A Study In Facial Features Saliency In Face Recognition: An Analytic Hierarchy Process Approach
  • Chapter 14
    Separable Convolutional Neural Networks For Facial Expressions Recognition
  • Chapter 15
    3-Dimensional Facial Expression Recognition In Human Using Multi-Points Warping
Readership: Students, academics, teachers and other people attending or interested in Facial Recognition
Melina Nicole Kyranides
Department of Clinical and Health Psychology, School of Health in Social Sciences, The University of Edinburgh, Medical School (Doorway 6), Teviot Place, EH8 9AG Edinburgh, UK

Kostas A. Fanti
Department of Psychology, The University of Cyprus, Nicosia, Cyprus

Kazusa Minemoto
Kokoro Research Center, Kyoto University, 46 Shimoadachi, Yoshida, Sakyo 606?8501 Kyoto, Japan

Sakiko Yoshikawa
Faculty of Art and Design, Kyoto University of the Arts, 2?116 Kitashirakawa Uryuyama, Sakyo, Kyoto 606?8271, Japan

E. Watson
Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK

and more...
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