challenges in face recognition
There are various challenges in face recognition. They include illumination. This takes place in the case of a slight change in lighting conditions affecting the come of face recognition hence impairing the results. In the time when the illumination try’s to be different if a similar individual gets captured with the same sensor and with identical facial expression and pose. The background is another challenge of face recognition (Xiong, 2018). This occurs when the background is positioned in the subject as this works by objecting to face recognition. The facial recognition system ought not to give it the required results outdoors when contrasted to what it provides indoors. This is due to the impacting performance resulting in the change as the locations change.
In some cases, the background of the picture might interfere with facial recognition by making it not to be noticed. The pose is another challenge that affects facial recognition (Xiong, 2018). Facial recognition is very sensitive to the pose. The movements of the head or different POV of a camera can invariably cause changes in face looks and produce intra-class variations creating automated face recognition across pose tough nut to crack. Another challenge is complexity. The reliance of the too deep convolutional neural network (CNN) architecture that is very complicated and unsuitable for real-time performance on embedded devices (Xiong, 2018).
Beyond security and surveillance purposes, where else do you think face recognition can be used?
Other than providing security and surveillance purposes, facial recognition has other various uses. For instance, it is used in marketing in business. Marketing is one of the business tenets that can be disrupted by artificial intelligence in many cases. The role that facial recognition plays isn’t only about the e-commerce app and showing relevant ads to them or text mining on the web for insights in the target clients. Facial recognition technology has taken a critical role on making it easy not only to sell but also to purchase when buyers are poised for choice or just aware of all features of various similar items (Xiong, 2018). Facial recognition solution is applied in much different business to market their products to a wide range of place. It is also used in attendance tracking and control: this helps in ensuring that any risks of insecurity are noticed, and hence security is maintained. Face recognition is very efficient in tracking attendance at individual teaching events that involve hundreds of attendees. Also, curbing truancy and it has the ability to ensuring the order is maintained wherever the teaching events is occurring. The face recognition app will pave the way for identifying a misbehaving attendee by just positioning the mobile phone in their direction. Face recognition for access control. It helps in controlling access to personal devices, residences, vehicles, offices, and other similar business places (Wen et al. 2016).
What are the foreseeable social and cultural problems with developing and using face recognition technology?
There are several foreseeable social and cultural problems with developing and using face recognition technology. Some of the issues are that facial recognition causes erosion of culture and society. This takes place by unveiling the culture of the people and the culture by making people apply the technology in the wrong way. There are limited individual privacy concerns. This leads to the societal problems of using facial recognition technology. The issue of data privacy concerns is minimal and hence making the cultural problems of the people eroded, thus causing such problems (Wen et al. 2016).