How much does it cost to create a facial recognition system?

Facial recognition systems are considered the most reliable among biometric identification forms, such as fingerprints and iris recognition. But the technology has its challenges. The facial recognition process often occurs in an uncontrolled environment with variable lighting conditions and dynamic backgrounds. Other factors affecting recognition quality include facial expressions, a person’s age, and ethnicity.

A facial recognition system has five main components:

Here is how facial recognition systems work:

After detecting a face, facial recognition software reads the facial geometry, which encompasses around 80 different elements. The key features include the distance between the eyes, eye socket depth, cheekbone shape, and jawline length. When the analysis is complete, the tool will generate a facial signature as a mathematical formula and compare it against other faces in the repository.

According to recent studies, facial recognition systems are reasonably accurate. For instance, the US National Institute of Standards and Technology achieved an accuracy rate of 99.88% with the Idemia facial recognition algorithm.

Facial recognition systems have many exciting applications in different industries. One simple example of this technology is photo tagging in Google Photos, where the tech giant compares faces in one image to a preexisting database of uploaded photos to identify users.

Let’s explore the four key factors.

Companies need to carefully consider their hardware choices to avoid getting their hopes high with a software solution that their devices can’t handle. But at the same time, firms shouldn’t overpay for computational resources that they will not use. To have a working facial recognition system, you will need to procure cameras, switches, and servers for data storage and processing (unless you’re planning to use the cloud). All these utilities will add up to your facial recognition system’s price.

The camera type and its location depend on the desired coverage, image quality, and angle of view. For example, if the device needs to capture a person standing one meter away, a 3-8mm lens camera is recommended. Examine the location where you want to install cameras. In the case of poor lighting conditions, opt for devices with built-in features that can compensate for the lack of light and still produce images that your facial recognition software can work with. Also, some facial recognition algorithms require 3D cameras.

You might consider purchasing cameras that come with pre-installed computer vision software and can accomplish tasks like pre-processing and face detection. This arrangement will take some load off your custom facial recognition software, increasing its speed. Such cameras can easily exceed $100 per device. Here is an example of what such gadgets can do:

There is no standard hardware configuration suitable for every facial recognition task. So, organizations need to consider their requirements carefully. If the chosen format is not powerful enough, it will cause delays and quality degradation.

Let’s assume the task at hand is to identify a person posing in front of a camera. To achieve this, we need two neural network models—a face detector and a face recognizer. We have to process at least six frames per second. Higher frame rates offer more accurate and realistic depictions. With these requirements, one could make do with a low-cost graphics processing unit (GPU), and even a central processing unit (CPU) might suffice. However, if we complicate this task by tracking people’s trajectories and actions or even increasing the number of cameras, we will have to procure a more powerful and expensive GPU.

Different types of ready-made facial recognition software are available on the market. These tools vary in their features and pricing models. Here are a few examples to help you gauge how much off-the-shelf facial recognition software costs:

You can see that different vendors offer variable pricing arrangements, allowing clients to select the suitable model based on the number of transactions planned per month, the speed of image processing, and the classifiers used.

It is crucial to note that face recognition software costs cited above account for subscription fees only, which are just a part of the overall expenses. Facial recognition solution vendors allow client companies to use their APIs, but you still need to integrate them into your system. You can turn to custom software vendors to facilitate integration and build a client-side application, which allows you to reap the full benefits of the facial recognition software. For example, integrating a third-party facial recognition tool that only does face detection and identification will cost you around $7,800, and this number will increase with the scope of the facial recognition solution.

You might also require additional features, such as enhanced security or on-premises storage, for sensitive applications where you can’t risk transmitting your data to the vendor’s cloud system. Computer vision development companies can help you build additional layers of functionality to supplement ready-made facial recognition solutions. For example, as part of a large project, we developed a microservice for anti-spoofing as middleware between the client-side application and the facial recognition software API. Such microservices cost around $10,000–$15,000, including development, training, and deployment expenses.

So, your final facial recognition software costs will accumulate everything mentioned above. Looking solely at software vendors’ licensing prices can be misleading.

Ready-made solutions are an excellent choice when you want to launch your product quickly and avoid spending on infrastructure. If you want a solution with specialized requirements, think of a facial recognition system at a hospital where some people wear a mask and some don’t. Then it is best to invest resources into building and training a custom facial recognition tool.

If a company operates from a remote location where different communicating objects are positioned far apart, you will need to establish a reliable communication channel. Such high-quality cables can be even more expensive than servers and cameras and will account for a large portion of the total costs of a facial recognition system.

We can reduce connection bandwidth requirements by installing the server responsible for video pre-processing close to the cameras and using proximity detection to avoid transmitting around the clock. We can also use Edge AI. In this case, the server will analyze the stream, extract images of interest, and transmit them further to the main server instead of streaming the entire video. This configuration can operate on 1-2 Mbit per second, even with multiple cameras, if there are no strict requirements on responsiveness and stability.

Logically, the more features you want to include, the higher the price. Some off-the-shelf solutions, such as Face++, set their prices based on the classifiers used, with more complex classifiers being more expensive.

The same applies to custom facial recognition solutions. The system may include classifiers, such as face detection, face verification, face grouping, similar face search, etc. The more models you accumulate, the more the final solution will cost. But the number of classifiers is only one of several attributes impacting complexity. Other parameters include the solution’s scalability, number of images being processed, security requirements, availability, and fault tolerance.

A simple solution that merely counts the number of faces in a picture will take one or two days to build and train. The costs of developing this type of face recognition app are $650–1,300, while more complex facial recognition tools can cost tens and even hundreds of thousands.

Here is one example of a rather complex facial recognition system. An enterprise risk management company based in the US reached out to ITRex to develop a comprehensive biometric-powered cybersecurity solution to identify people based on their unique facial features. Our team opted for Microsoft Face API to deliver a solution with a diverse set of functions. We built a system that relied exclusively on biometric parameters as cyber credentials. It offered secure data transfer and storage space, a person-to-person live video interaction channel, and had its own proprietary cybersecurity protocol that can be used by third-party software. This system could also operate in high-load cloud environments and included microservices that enabled painless scaling and change implementation.

The costs associated with such a facial recognition solution could easily surpass $500,000.

System complexity directly influences the cost of facial recognition software. You can deploy a doorbell camera bundled with an associated cloud solution and a white label mobile app for a few thousand dollars. While a highly complex and secure solution will cost you up to $500,000 or even more. The location of operations also influences the total price. If you need to survey large warehouses with hundreds of cameras, hardware costs will form a large part of your expenditures.

But even with complex solutions, you can plan ahead to ensure the allocated budget is wisely spent. Don’t make the mistake of opting for a cheaper tool only to end up spending more on security fines than you saved on the software itself. And those fines can be rather hefty. Not long ago, the UK’s Information Commissioner’s Office (ICO) charged a prominent American facial recognition company, Clearview AI, with £17 million in penalties as it failed to obtain consent when gathering publicly available photos of British citizens and using them in training datasets.

Here are a few tips that will help you make cost-effective decisions:

To sum up, the amount of money necessary for facial recognition software depends on multiple factors. And if you can take all of them into account, you will have a more realistic idea of what you can get with your budget. Don’t limit yourself to what is available on the market. If you have rather unique requirements, turn to custom software developers for tailored solutions.