Facial Recognition And Thatcher Effect

Facial recognition is a technological product of the digital age that is continuing to evolve. The efficiency of the technology is an asset to crime detectives apprehending criminals, or the government tracking suspected terrorists for the safety of the country. It can also be used on a corporate level to allow a business to understand their ideal customer, or to increase the intractability of their website. While these abilities are positives to the people using them, the data collection may be harming more than it is helping. Considering the benefits of facial recognition, it is important for people to see what they are giving up for a more efficient experience. Facial recognition technology forces users to relinquish control of their own

In the present contemporary era, facial recognition technologies are being installed by the companies in an extensive sense that surely reflects a continuum of growing hi-tech superiority and complexity. At the most ordinary level, facial detection is done by this technology which means that a photo is just detected and located for a face ("Facing Facts: Best Practices for Common Uses of Facial Recognition Technologies," 2012).

Secondly, face recognition units contain stored descriptions of known faces. When a familiar face is seen, face recognition units send signals to cognitive system and active person identity nodes. Person identity nodes allow access to semantic information about the person. The impairment

These organizing principles will determine how the elements in a scene will be grouped together..The role of the Gestalt principles in perceptual organization gives everyone the ability to see objects as continues, simple, similar, and proximity. Continuation allows the human brain to look at a coil of rope as one continuos rope and ropes that overlap each other as two separate strands of rope. If a person did not have the ability of continuation simple processes would take a lot longer while a person uncoiled the entire ropes to make sure that it was one continuos rope. Pragnanz gives a person the ability to look at something in a simplier form when there are more complex ways to look at it. Such is the case with the Olympic five circles, the prananz theory gives the human the ability to see it as five rings flowing together but the brain without the ability may look at it as nine different objects that did not have any flow or connection to them at all. Similarity is when similar items will appear to be grouped together. Grouping can occure when there are items that are of similar shape, size, or orientation. Proximity is very important on how the brain can group similar object together and how by changing the color of some objects will redirect the brain to a different patternization. Such is the case when a block of dots that are 7 high and 7 wide. If all of the dots are the same color the perception in the brain would group them in a horizontal pattern but once

Law of Proximity states that the brain associates objects close to each other than it does when objects are spaced far apart.

The studies conducted by Northwestern say that brain activity increases in the first 200 milliseconds when we first interact with a person from our same race or from a different race. The studies say that there is a time right after a person meets another of the same race or a different race that determines whether the face is remembered or even forgotten. The point where the brain begins to remember or forget the memory is almost immediately after a person first sees the face. People also remember people by their attributes for example, you might see that a face reminds you of someone you know. You may see that the persons expression appears kind or afraid, or it looks like the face of a famous athlete or a singer. Being able to identify people's attributes increases the likelihood that a face will be

The face recognition model developed by Bruce and Young has eight key parts and it suggests how we process familiar and unfamiliar faces, including facial expressions. The diagram below shows how these parts are interconnected. Structural encoding is where facial features and expressions are encoded. This information is translated at the same time, down two different pathways, to various units. One being expression analysis, where the emotional state of the person is shown by facial features. By using facial speech analysis we can process auditory information. This was shown by McGurk (1976) who created two video clips, one with lip movements indicating 'Ba' and other indicating 'Fa'. Both clips had the sound 'Ba' played over the clip.

Face recognition is another biometric technology. Face recognition uses the same technology that iris recognition uses. For face recognition, a camera takes several images of a person to find out who it is. Face recognition differs from all of the other biometric technologies because the person that is in the picture does not have to cooperate with the process. In all of the other technologies it requires the people to actively participate in the process. In face recognition, the image can be taken without the person even knowing that it took place.

Through this routine of advanced technology analysis, it has been established to increase the results and have hastened the procedure of identifying suspects of crimes. Facial recognition is also necessary for public involvement and observation as it also aids law enforcement officials to more easily zone in on possible suspects of a crimes being caught. With the use of facial recognition, it constantly has been proven quite an effective method with the incorporation of this technique.

This essay will talk about face recognition and several reasons why it has been studied separately. The ability to recognise faces is of huge significance of people’s daily life and differs in important ways from other forms of object recognition (Bruce and Young, 1986). Than this essay will talk about the processes involved in face recognition which comes from the diversity of research about familiar and unfamiliar faces-it includes behavioural studies, studies on brain-damaged patients, and neuroimaging studies. Finally, it will discuss how face recognition differs from the recognition of other object by involving more holistic or configuration processing and different areas of the brain (Eysenck & Keane, 2005).

Prosopagnosia is defined as the difficulty in recognizing an individuals face; it is broken down into 3 main types; Apperceptive prosopagnosia, associative prosopagnosia and developmental prosopagnosia. Perception is an important aspect when recognizing faces, without recognizing the stimulus (face) you would not be able to identify a person. Therefore the individuals who sufferer from this disorder is unable to accurately recognize a face whether that be the face of a familiar person such as a family member or close friend, the face of a famous person, or even their own face. This paper will look at prosopagnosia in greater detail, it will explain the 3 main types, as well as give insight as to why face recognition is important in our

Bruce and Young’s theory of recognition tells us that human’s extract several kinds of information from faces; and that there are eight different components of such information. Such as structural encoding, expression analysis, facial speech analysis, directed visual processing, face recognition nodes,

Automatic face recognition has always been a major focus of research for a few decades, because of numerous practical applications where human identification is needed. Compared to other methods of identification (such as fingerprints, voice, footprint, or retina), face recognition has the advantage of its non-invasive and user friendly nature. Face images can be captured from a distance without interacting with the person, which is particularly beneficial for security and surveillance purposes. Furthermore, extra personal information, like gender, face expressions or age, can be obtained by further analyzing recognition results. Nowadays, face recognition technology has been widely applied to public security, person verification, Internet

Similarly, both theories are supported by research. Lawson and Humphreys (1996), for example, showed that recognition is affected more by tilt of major axis (foreshortening) than any other rotation, which endorses Marr’s and Nishihara prediction that establishing a central axis is crucial to the process of recognition. Warrington and Taylor (1978) reported that brain damaged patients could recognize objects presented in a typical view only. These patients found difficult to say if two photographs presented simultaneously were the same object when one image was a typical view and the other an unusual view. Although this could be explained as the patient’s inability to transform a 2D version of the atypical view into a 3D model, it could also be due to difficulty in establishing the central axis or due to some features of the object being hidden. In a later study, Humphreys and Riddoch (1984) used images where either the axis had been foreshortened through rotation or a critical feature was hidden. They found that patients had more problems recognizing the images with a foreshortened axis than the ones where a critical feature was hidden. Their

Although some critiques can be made, the experiment overall was well structured and the scientists was able to gather good evidence. The authors agreed that the mechanism that is associated with the implicit recognition is different from the recognition awareness. The scientists had the participants take a forced-choice test for a second time after they had looked at the kaleidoscope images. By doing another experiment using the same technique, they are giving a variety of stimiulus that could reaffirm the correlation that they are trying to make.