3D Face Recognition vs 2D Face Recognition

The facial recognition system is one of the features of "smart technology." It's employed for situational monitoring and crowd-spotting criminal activity. Managers and security officers are being replaced entirely by biometrically read video surveillance.

It is utilized in stores, train stations, airports, medical facilities, educational institutions, and businesses generally where employee safety and control are necessary. Let us explore 3D face recognition Vs 2D face recognition.

Even though 2D face recognition research has advanced significantly in recent years, human positions and lighting still have a major impact on accuracy. The accuracy of the recognition will be lower in low light conditions and when the faces aren't aligned correctly in the camera view.

An alternative approach to face recognition that may be able to get above the basic drawbacks of 2D technologies is made possible by the rapid advancement of 3D sensors. Under challenging circumstances for 2D technologies, the geometric information in 3D facial data could significantly increase recognition accuracy. A new trend in the study has emerged as a result of numerous academics focusing on 3D facial recognition.

2D Face Recognition

A two-dimensional image is created by 2D technology. With a minimal collection of physical and mathematical features, the program for facial recognition analyzes the parameters of the face and generates images.

Advantages and disadvantages

Because of their affordability and effectiveness, 2D algorithms are the most widely used on the market. High demand drives the technology's developers to continuously improve it.

• The current high mistake rate is one of the shortcomings.
• False pass percentage: 0.1%;
• 2.5% of fake rejections.

3D Face Recognition

3D produces images that are of greater quality and are three-dimensional. There are various methods for removing faces:

• Laser
• Scanners with lighting and digital image bending processing.
• Scanners that utilize photogrammetric technology.

Advantages and disadvantages

High reading accuracy is a characteristic of 3D technology. The false-pass rate is 0.1%, while the false-pass rate is a pitiful 0.0005%.

However, more advanced tools and development techniques are needed to achieve this level of accuracy in the work. Consequently, the drawbacks are:

• The requirement to buy pricey cameras to keep the 3D feature;
• The lack of compiled databases containing the identities of individuals, which makes real-time analysis extremely difficult;
• In terms of personality recognition, the twins' percentage difference is essentially negligible.

3D Face Recognition Vs 2D Face Recognition?

3D recognition outperforms 2D recognition in terms of sophistication. The real benefits of 3D recognition over 2D recognition include the following important characteristics.

The 2D method cannot identify a face if the participant is not directly facing the camera. An inaccurate identification of a person may arise from a change in the camera angle or face position. To construct a model, laser 3D identification systems take multiple faces in varied positions, with the nose serving as the center of detection. Thus, it can identify an individual from various points of view. In terms of ID authentication, security, and monitoring, it is beneficial.

3D has a Greater Feature Set

To enable identification, features or characteristics acquired from a face must be sufficient. The accuracy of recognition rises with the number of features. A strong database of faces is produced via 3D recognition, which builds the 3D model of the image by reading geometrical features, depth, and curvature.

Which is Better, 3D or 2D Liveness Detection?

To determine whether a face is alive, the 2D recognition approach requires an additional sensor or algorithm that works independently of the actual 2D camera algorithm. However, 3D produces a digital model of a face in three dimensions, which suggests that the face is partially real. When it comes to presentation attacks such as false visual presentations, the 3D model itself is resistant.

Financial Considerations

3D technology is a little more expensive than 2D in terms of system cost. However, when you consider the other benefits like liveness detection, accuracy, and simplicity, the price increase becomes insignificant. Accurate detection lends credibility to any firm, which in turn means improved return on investment. Moreover, the capability to identify a face from multiple perspectives reduces the number of cameras used in a closed circuit.

Motion Study

A 2D face shot and a 3D face can be distinguished from one another using motion analysis. Compared to a 3D object, a plane 2D object moves very differently. To enable the system to do motion analysis using optical flow, a video is recorded.

Texture Analysis

To distinguish between real and fake faces, the system analyzes for print failure and image blur. The texture of an actual 3D face differs significantly from a face image printed on a 2D piece of paper.

To recognize the actual facial texture, the system needs to be provided thoroughly. Better outcomes are obtained when this is paired with the motion analysis.

Online payment authorization is advised to use 3D Depth-sensing, the safest facial unlock method available. Except in the case of a twin, it is more secure, accurate, dependable, and resistant to being misled by printed images or unrelated photographs. For this reason, 3D face unlock systems are typically more expensive.

Best Face Recognition Software

Lystface is the leading facial recognition software to fulfill business needs. It is cost-effective and user-friendly software to meet the requirements of all industry types. Employees can be monitored with an accurate facial attendance system with more features.

Bottomline

In both the academic and commercial sectors, 3D face recognition is the most researched field. Enhancing AI to recognize and produce a better 3D reconstruction of a face is the subject of an increasing amount of study. Shortly, 3D facial recognition will be widely used in security, surveillance, automated driving, aviation, and access control.