University of South Wales: Facial Recognition System Presentation

This presentation provides a comprehensive introduction to Facial Recognition Systems (FRS). It begins by explaining how FRS works, detailing the algorithmic processes involved in capturing, reading, and comparing facial features. The presentation then explores the various methods used in FRS, categorizing them into geometric, appearance, and template-based approaches. A significant portion is dedicated to the wide-ranging applications of FRS, including its use in public security, law enforcement, credit card verification, and access control. Furthermore, the presentation outlines different face recognition algorithms and highlights key challenges and issues, such as pose variations, security, and privacy concerns, offering a well-rounded view of the technology.

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Facial Recognition Systems
Introduction to Facial Recognition System
Facial recognition system (FRS) is a technology
that is capable of identification and verification of a
person from a particular video frame, image source
or a video source (Parmar and Mehta 2014).
Face Recognition Methods
Challenges/Issues associated with Face Recognition
The key challenges associated with the field of Face
Recognition are indicated as follows-
1. Pose Variations can be challenging for
automated face recognition (Bendale and Boult
2015)
2. Presence or absence of structuring elements can
affect the automatic facial recognition process
3. Facial Recognition system gives rise to certain
security and privacy issues (Fu 2019)
4. Facial data can be collected and stored without
the knowledge of the owner
5. Government agencies have an ability to track an
individual, risking the basic freedom of an
individual (Masi et al. 2018)
6. The facial signature can end up in many places
due to increase in prevalence of facial
recognition systems
How Facial Recognition System Works?
Facial Recognition works on a grand algorithmic
scale. The algorithm matches an input with the data
stored on a database (Happy and Routray 2014).
The basic steps involved in Facial Recognition are
indicated as follows-
Step 1: Input- A picture is captured from a photo or
a video
Step 2: FCR system reads the geometry of the face
(the input)
Step 3: The facial signature, which is a
mathematical formula is compared with the stored
database
Step 4: A conclusion is drawn
Application of Facial Recognition System
In Recent years, the use and application of Face
Recognition Systems has considerably increased
The Key areas of application of FRS are indicated
as follows-
1. It is widely used in Public Security
2. FRS is used for Law enforcement and
Commerce (Amos, Ludwiczuk and
Satyanarayanan 2016)
3. It is used for Credit card Verification
4. It is used for Criminal Identification
5. FRS has wide application in Access Control
6. FRS is further used in Human computer
intelligent Interaction
7. It is used in Digital Libraries and Information
security (Cohn and De la Torre 2015)
Face Recognition Systems are used worldwide for
preventing fraud and for securing public Safety
References
Amos, B., Ludwiczuk, B. and Satyanarayanan, M., 2016. Openface: A general-
purpose face recognition library with mobile applications. CMU School of
Computer Science, 6, p.2.
Bendale, A. and Boult, T., 2015. Towards open world recognition. In Proceedings
of the IEEE conference on computer vision and pattern recognition (pp. 1893-
1902).
Cohn, J.F. and De la Torre, F., 2015. Automated face analysis for affective
computing.
Fu, K.S., 2019. Applications of pattern recognition. CRC press.
Galbally, J., Marcel, S. and Fierrez, J., 2014. Biometric antispoofing methods: A
survey in face recognition. IEEE Access, 2, pp.1530-1552.
Happy, S.L. and Routray, A., 2014. Automatic facial expression recognition using
features of salient facial patches. IEEE transactions on Affective Computing, 6(1),
pp.1-12.
Masi, I., Wu, Y., Hassner, T. and Natarajan, P., 2018, October. Deep face
recognition: A survey. In 2018 31st SIBGRAPI conference on graphics, patterns
and images (SIBGRAPI) (pp. 471-478). IEEE.
Parmar, D.N. and Mehta, B.B., 2014. Face recognition methods &
applications. arXiv preprint arXiv:1403.0485.
.
Face Recognition Algorithms
Personal Information
Name: Pattan Rizwana Tabassum
Student ID: 16053028
There are several different kind of methods for
facial recognition, which are indicated as follows-
1. Geometric Based/Template Based
2. Piecemeal/ Wholistic Based
A FRS generally make use of biometrics to map
the facial features from a particular image or a
video.
Facial Recognition is considered to be an
effective method for verifying the identify of a
person (Galbally, Marcel and Fierrez 2014)
Algorithms used in Facial Recognition Software
mainly identifies the facial feature by extracting the
and identifying the features from the subject’s face.
The algorithm identifies, analyses and examines the
relative position, size and shape of the eyes, nose,
jaws, cheekbones and other part of the face
The Different face recognition algorithms that are
used in Face recognition systems and software are
indicated as follows-
1. Classical Face Recognition Algorithm
2. Artificial Neural Networks in face recognition
3. Gabor wavelet‐based solutions
4. Face descriptor‐based methods
5. 3D‐based face recognition
3. Appearance Based/ Model Based
4. Template / Statistical / Neural Networks Based
Method