Advanced technologies appear each year, and modern people need to learn what those are to be able to enjoy all the advantages the solutions provide. We’d like to devote this article to the facial recognition framework, so you could enjoy it straight away.
Let’s start exploring.
Face recognition operating principles
When one refers to face recognition, we shall consider two operations: firstly, pixels get processed, and then pictures are matched. Meaning, the face of a person who got on camera is to be compared to a complete database of all photos that were recognized and saved earlier.
Elements required to apply human face recognition mechanisms
To guarantee proper operation of face recognition services, one shall include such components, as:
a regular camera – since every cell phone and almost every tablet has a built-in camera, there won’t be any troubles with this point;
a heavy server that will be powerful enough to store the full database;
robust algorithms to compare and recognize photos;
a trustworthy neural framework having access to millions of pictures providing specific notations.
How one can identify a human face
There exist various techniques to attain the desired:
2D recognizing. The mechanism is pretty popular. It applies and compares pictures in two-dimensional formats.
3D recognizing. The approach is getting more and more demanded. Solutions, like, Apple’s Face ID, take advantage of the technologies and re-construct 3-dimensional photos.
Face recognizing in a controllable backdrop. The method assumes the background doesn’t move, thus, the technology can easily isolate specific pieces, for instance, eyes and nose, to reconstruct the face itself.
Faces searching based on colors. If you want to create a successful app having such technologies, you need to know that the algorithm will scan the picture to determine areas of skin color for identifying a face.
Faces searching by motions. When you deal with video images (the ones that have motion effects), you’ll need this technology which is able to identify particular benchmarks – say, moving eyebrows, forehead and blinking eyes. Such reference points shall help with face identification and database comparison.
The imager recognition. Thermal imaging is widely used to detect faces, and those devices get improved each year.
What are the phases of human face recognition?
For a better understanding of how such technologies function, we’d like to distinguish the key stages of the process.
Primary face detection. The first task is to find a face in the photo. The software doesn’t identify a person yet. The idea is solely to detect a face.
Determining benchmarks. This stage is more sophisticated. The objective is to define the specific individual characteristics of a person in the picture. Eyes used to be the only reference points, however, nowadays there exist over 70 diverse benchmarks to determine human faces.
Reconstructing a front-end face. Based on reference points determined previously in order to match pictures a frontal face image has to be built.
Descriptor computing. The time is to get the descriptor calculated. Descriptor represents specific characteristics to describe a particular face, however, such parameters, as hairstyle and age aren’t taken into account. To ensure high accuracy level a specific digital photo – so-called, a face vector – shall be used to compare to.
Face comparing. Finally, we get to the comparison phase, when digitized face vector is to be compared to photos from the database.
Face recognizing. The last stage is identification. When the match from the database is found, a person could be identified.
So, now after having learned more about facial recognition technologies, we shall figure out how such software could be applied to the best advantage, shall we?
Ideas on face recognition application
Every service and each technology has its target demographic and its markets. The knowledge of those shall help build a successful solution. We’d like to specify the sectors where facial recognition platforms can bring the most to its owners.
All people could be divided into two groups: those who advocate for a healthy lifestyle and those who don’t. The first camp needs specific technologies to monitor what they eat and calculate calories, thus, they’ll be happy to take advantage of image recognition services.
Just think of it… You take a picture of your meal by means of your cell phone and the app provides you its analysis, including calorie calculations. It may sound like magic, but Calorie Mama already does that. The database of that image recognition service provides data on multiple dishes, thus, the audience enjoys the possibility to check nutrition values at a moment’s notice.
Who doesn’t know Google’s Image Search? The solution helps with picture searchings. Let’s say, you’d like to know what platforms have copies of a certain picture. You simply upload that picture to see the list of those websites.
However, Image Search of Google isn’t for face recognition, but as to image recognition, no one shall double in its reliability and accuracy.
Here the algorithm is similar, but this time it’s about products customers would like to buy.
ScreenShopit is the one to offer its API for e-stores to facilitate its searching mechanism. Moreover, machine learning adds even more efficiency to the shopping process.
CamFind in its turn allows find out specific data on an object. After having taken the picture of that item and having uploaded it, users can:
locate that object in stores;
find analogous items;
get some content related to that object and more.
Additionally, the audience might enjoy sharing their findings with each other.
People who are fond of gardening and care for the environment will also take advantage of picture recognition platforms.
When bumping into an unfamiliar tree or a flower, a user can easily find out all its properties immediately. All they have to do is to take a picture of that plant and upload it to an app, and all data available shall be provided.
Garden Answers Plant Id, LeafSnap and more programs offer such services already.
Picture recognition solutions can even enhance users’ vocabulary.
Have you heard of ImageTranslate? The solution is actually convenient. The audience uploads a picture and, after making a few taps, get the translation of items in that picture. That’s impressive.
This concerns facial recognition platforms, and we’d like to mention several great representatives.
Betaface was designed specifically for media businesses. The solution assists in locating specific persons and getting data on them. Of course, we’re talking only about the info available online. Users can also enjoy its possibility to find a looking-alike person from a celebrities database, and every picture will reflect the matching percentage.
One more great solution is Blippar. As a matter of fact, it’s an AR service with face recognition functionalities. The program recognizes people and finds their accounts on various social networks. Thus, the software provides data on users’ likes and preferences.
So, cannot wait to enjoy all the possibilities face and image recognition technology grants? Go for it!