User:Ywolansky/sandbox

== Face Detection ==

Face Detection
Facial detection is an advanced computer technology program that is being used in a variety of applications that has the ability to identify human faces using digital images. An example of this face detection is in recent Microsoft computers and Apple iPhones that allows users to log into their computer and or phone without a passcode, by simply showing the computer and or phone their face as a form of entry onto their device.

Face Recognition Technology
Face Recognition Technology (FERET), is a program that focuses on developing facial recognition algorithms. This program was designed to measure the performance of algorithms by giving it three evaluation tests.

The first evaluation consisted of three subtests that include examining the ability of the software to recognize faces based off a photo gallery of over 300 individuals, its ability to reject a face that is not in the gallery, and finally to test its ability to recognize an individual from different angles and poses.

The second stage was to enlarge the photo gallery by almost three times the size it was before with duplicate images.

Lastly the final evaluation was to require the algorithm to match a set of over three thousand images compared to another set of over three thousand images.

How facial recognition is used in crime fighting:
The Unites States Government Accountability Office (GAO) reports that the FBI mainly uses face detection as an external system to help law enforcement investigations. There are five sections, each being different.

The first “appendix” as they call it, is about their objectives and methodology.

The second appendix writes about face recognitions and its statistic.

The third states the FBI’s facial analysis, comparison, and evaluation.

The fourth has comments from the department of justice.

The fifth and final appendix states where you may contact the staff who was involved in this project

Facial recognition technology helps nab criminals--and raises privacy concerns by Wendy Davis. This article is about how facial recognition helped convict James Robert Jones, a former soldier who had been sentenced 23 years in prison for stabbing and killing another soldier, 40 years after he escaped military prison. Jones moved to Florida and gave himself the new identity of Bruce Walter Keith. However the newly created technology that caught Jones identifies people based on photos taken of them ranging from state agencies to surveillance cameras. The software used relies on algorithms to compare photos and determine whether or not is is the same person. Despite this recent release in technology, there are its mistakes with privacy issues. This type of technology will continue to be used and improved for future criminal tracking and many more.

How facial recognition is used in modern day computers:
 This Awesome Facial Recognition Technology Could Replace Passwords by Laura Stampler. This article writes about how facial recognition is very convenient and makes it harder for people to hack into your computer. It also makes it harder to forget your password because your face is the password. This new password alternative is known as “facelock”, which is based on the psychology of facial recognition. Psychological research has proven that even though people can recognize a large variety of photos of the same person, however faces that they are unfamiliar with, are associated with a specific image. If you were to see the same stranger in multiple action shots that are all different from each other, it would almost seem like they were a different person. In order to use Facelock, researchers experimented with users to flag a set of faces that they are familiar with, but others may not have the same impression. To unlock whatever device they are trying to log into, the user would simply be required to identify said face on a series of grids. By doing this, it trains the program to recognize your face. With follow up research, results showed “that the faces were easily identified 97.5% of the time with an 86% success rate a year later” (Stampler, 2014).

Face detection and recognition: theory and practice:
Published in 2016 by Asit Kumar Datta, this book explains the theory and practice of facial detection and recognition programs. The book first introduces the concept of this idea by offering a general layout of what future research this can bring to cognitive neurophysiology. The text then transitions to exploring the face imaging process, the statistics involved in creating the technology, and the use of artificial intelligence. It also discusses the methods used for recognizing face landmarks that help detect a face, methods of generating a synthetic face, and the testing and training systems needed to make sure their product works efficiently.

Uncertainties of facial emotion recognition technologies and the automation of emotional labor
By Thomas Bøgevald Bjørnsten, this article is about how automated recognition and detection of faces have been implemented in a broad range of media platforms. They go into depth about the analysis of emotions from facial expressions using computer based systems, in relation to theories of basic emotions. Bjørnsten also explores the uncertainties of processing the human face ‘as an image’ and how it is a temporary and static image. It is also a style of combining a number of parts simultaneously, each of them forming an individual frame and pixel with each other creating an expression. One of Bjørnsten’s arguments addresses the temporal character of human emotions and how we have created algorithms to regulate types of discretization, which is a mathematical process of transferring continuous functions, variables, and equations into separate counterparts, in order to prompt specific patterns of emotions and their responses and expressions.

Use of Facial Recognition Technology for Medical Purposes: Balancing Privacy with Innovation
By Seema Mohapatra is about the possibility of using facial recognition when you apply for a medical job. The employer, or interviewer, would require the interviewer to submit a photo of themself as part of the application. The employer would then put the picture submitted through a recognition software program that has the ability to scan for common genetic diseases and estimate your longevity. If the results indicate that the applicant will pass within the next decade, the employer could deny their application. Despite how fictional this may seem, in June 2014, Oxford scientist reported to have developed a facial recognition software that has the ability to examine ordinary photos of people and diagnose rare genetic conditions if it applies to them.