Human Detection Paper

Biometrics technology aims at utilizing major and distinctive characteristics such as behavioral or biological, for the sake of positively indentifying people. With the help of a combination of hardware and specific identifying sets of rules, a basic human attribute, automated biometric recognition mimics to distinguish and categorize other people as individual and unique. But the challenges surrounding biometrics are great as well.

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).

I chose to analyze the case study, Tug Of War that was written by Yossi Sheffi and is found in the Harvard Business Review.

In effect, people are unknowingly being put in suspect lineups without their awareness or consent. This can lead to false accusations against innocent citizens. Most police departments still rely on officers to verify that the suspect chosen by the face recognition software actually matches the camera footage. However, humans shockingly make an error in this process once in every two cases (Bedoya, Alvaro, et al 2016). In some instances, it is not only this human error that is leading to their conviction but rather the system itself. A study, co-authored by the FBI, said that the facial recognition software is actually less accurate when it comes to identifying African Americans. Systems relying on mugshot databases have a disproportionate number of African Americans due to their high arrest rates in America. This creates “racial biased error rates,” that perpetuate implicit and systemic racism in our society (Bedoya, Alvaro, et al 2016). But for American citizens in general, in any crime being solved by using face databases, anyone is a potential suspect. Because of this, regulations should be put in place to limit the use of this technology to cases where its use is relevant and vital to solving the issue.

The brain identifies what it sees in a series of steps. The brain makes a feature map of the eye breaking the visual field into sections. Information collected in a particular section of the visual field will always be sent to the

If the obstacle is in the range of the sensor , the obstacle is detected .When the system detects obstacles, the speed of the vehicle is reduced to zero and an image alert is displayed in the smartphone along with voice output, which means that the detection is successful. If there is no obstacle ahead, there is no outcome. If the obstacle is out of the range of the sensor , there is no outcome and the detection fails.

In general, the police can conduct three types of identification procedures: line-ups, show-ups and photographic arrays. In order to conduct a line-up, the suspect must be presented to the witness with five other people with similar physical characteristics, clothing worn, and race; the victim or witness then identifies the suspect. The show-up identification procedure is usually conducted when the suspect is detained a short time after they committed the crime; they are then brought to the victim or witness for identification. It is also conducted when the victim or witness is immobile and unable to attend a line up. The photographic array procedure requires the picture of the suspect and five other people with similar physical

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.

A GPS is used, to get a rough location of the car, at which point radar, lasers and cameras take over to monitor the world around the car, 360-degrees. The software can recognise objects, people, cars, road marking, signs and traffic lights, obeying the rules of the road and allowing for multiple unpredictable hazards, including cyclists. It can even detect road works and safely navigate around

Identifyer is a cellphone application that aims to help high school students identify their interests and careers. To help the high school students who still have no idea what they want to do in the future, Identifyer provides abundant resources and information for them, including advanced tests, basic information of industries, working experience sharing, company visits activities, short-term experience programs and professional training courses.

face detection: this aims at finding faces in images (or indicate if a face is present)

In this survey, mainly exposes the different types of face annotation techniques. Face annotation is an exigent problem in the field of image analysis and computer vision has established many applications in different domains. Face annotation (or “face image tagging”) is becoming growingly popular both on the web and many organizations. A face annotation is defined as the image providing information about the facial images. Face annotation system is trying to attach a label to each and every face images in the database. The most important use of face annotation is to manage and organize the huge number of facial images collections in several organizations.

Their theory has enough empirical evidence although it lacks the initial face detection stage and can be said to be inflexible, with limited case study size resulting in the findings having the possibility of lacking generalizability.

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