How a Facial Recognition Technology Work?
Facial recognition technology uses a CNN (Convolutional Neural Network) to manage images, videos and spatial data. CNN is a deep-learning model that extracts, analyzes and identifies facial data at a more detailed level. It uses advanced algorithms such as MTCNN (Multi-Task Cascaded Convolutional Networks) or YOLO (You Only Look Once) to detect and recognize faces in real-time.
CNN uses deep learning models to analyze and extract unique features of an individual`s face. Then it compares the features with the known faces registered in the database. CNN transforms face images into numerical vectors which are referred to as embeddings. So, the comparison is done by calculating the distance between feature vectors and different embeddings.
With the advancements in deep model technology, facial recognition is getting smarter in capturing more facial signatures and landmarks specific to an individual facilitating deeper recognition of images, lighting and angles. These signatures are represented in compressed numerical representations. These distinct numerical representations of unique facial features facilitate rapid and more precise comparison to known and variant faces.
5 Interesting Facts on Facial Recognition with Artificial Intelligence
With the advent of AI, face recognition technology has reached new heights. Integration of AI and ML in facial recognition has automated the process of detection and identification of an individual or object in real time using a series of images and videos. It can recognize a person from a group of people in the image or video and understand the place by identifying the surroundings with accuracy and speed. AI automatically extracts, classifies and identifies data from an image or video to pinpoint an individual. It processes videos, images, 3-D data and satellite images to identify and detect a person and his exact location. It can also identify objects and goods with accuracy now.
Most importantly, machine learning has been working at full pace constantly improving the present face recognition models. The facial recognition models are exposed to huge data of images and videos. These models use refined algorithms to extract, identify and classify facial data. Due to this, it has been able to guess the age, expressions, emotions, and environmental conditions of the people it is analyzing in the images. These advancements added new dimensions to facial recognition technology.
Here are five interesting facts about facial recognition with artificial intelligence:
1. No Touch Needed
Most importantly, machine learning has been working at full pace constantly improving the present face recognition models. The facial recognition models are exposed to huge data of images and videos. These models use refined algorithms to extract, identify and classify facial data. Due to this, it has been able to guess the age, expressions, emotions, and environmental conditions of the people it is analyzing in the images. These advancements added new dimensions to facial recognition technology.
2. Reads Emotions
The earlier system was only equipped to recognize a person but now it is capable of reading the emotions and feelings of a person. AI is fully capable of reading facial expressions, contours, muscle contractions and eye moments to understand the emotions and feelings of a person in certain situations. It can figure out whether you are happy, sad, angry, anxious or nervous. Mental health experts are utilizing this technology to read the mental conditions of a person in different conditions and interactions.
3. Access Control Security
Companies manufacturing smartphones, tabs, laptops, computers and different types of doors of entrance in public places, banks, schools, hospitals and homes are using AI-powered face recognition technology to protect access controls and recognize individuals with different feelings. It prevents strangers and unsafe elements from accessing the gateways using the AI-powered lock system. Even different types of vehicles are fitted with this technology to prevent thieves and criminals from getting unauthorized access. Due to this, the real owner does not need to remember passwords or passkeys with him to access what is his own.
4. Better Security Cameras
AI-driven security cameras work more precisely in scanning and analyzing a huge number of videos in real-time to find out facts and figures about a person for suspicious activities. It can spontaneously detect known people and their unusual behaviour by reading their facial expressions and feelings. Sensitive organizations such as banks, hospitals, education institutions, state organizations, and big tech companies are installing this technology in their entrances and critical zones to catch malicious people and protect access control.
Additionally, it has a great potential to transform military security in border areas, and war-torn countries to detect enemies and their suspicious activities. Fitted with multilayered scanners and advanced facial detection technologies it can easily pin down the enemy and suspicious individuals. Hence, high-tech security cameras can enhance border security and equip the guards with a better surveillance system.
5. Privacy Concerns
As AI evolves, and takes over facial recognition technology a new debate sparks over privacy concerns and the ethical use of this technology. Social thinkers are concerned about individual privacy, data security and potential biases. Moreover, it raises questions about cameras flagging someone innocent as a bad actor due to some technical flaw or data overlap. If the innocent is targeted then who would be responsible for the resulting loss and damage? What if the technology falls into the hands of bad actors who exploit it to breach privacy and steal the personal details of a person?
Government authorities have to ensure that this technology is used ethically and for the good of all. There have to be proper privacy protocols and controls so that no one can misuse this technology to do any type of malicious activity against innocent people. Then there must be effective solutions to deal with the biases and discriminations AI and ML develop when it is fed with data that carries the signs of impartiality. The discriminatory and hateful content will manipulate the AI tools, make wrong decisions and target people with specific traits and features. So, this issue needs proper attention before we fully implement AI-powered facial recognition in our day-to-day usage.
