Face Detection Software

The Best 8 Free and Open Source Face Detection Software Solutions

The Best 8 Free and Open Source Face Detection Software Solutions

Technology never ceases to amaze us. Pattern recognition and image processing is one area that has been in huge discussion and research these days. The evolution of the biometric authentication solutions offered an antidote to inconvenient, clunky, and easy-to-forget passwords. It helped the enterprises, schools, community homes, offices, and residential areas to keep their premises protected using the right security technology. Face detection is one among those prominent biometric solutions that involve identifying human faces in digital images and videos. Once the face is detected, the AI then provides the information on its size, pose, and location. All this is backed-up by the advanced best face detection software tools and facilitated as per the algorithms of Facial Recognition Technology (FRT).

The concept came into context in the year 2001, when Paul Viola and Michael Jones introduced the object-detection framework. The framework aimed at detecting objects in real-time, and the problem of face detection primarily motivated the outcome of the required solution. Today, the Facial Recognition Software Market is likely to touch USD 11.30 Billion by the year 2026.

This article will reveal the most critical aspects of the best face detection software systems and their importance in various industries. This article aims to help you understand how useful free and open-source face detection tools are in today’s competitive market environment.

Face Detection Technology

The fastest biometric-based face detection technology comes with the only purpose, i.e., to identify human faces. Today’s face detection and recognition systems are far better than the fingerprint readers and eye scanners. These systems analyze the characteristics of the facial images of a person that were taken using a digital video camera. For example, the CCTV cameras installed at the security check area in an airport can trace the record of matching photos of every passenger attached to the passport with their faces.

Face Tracking

How does Face Detection Technology work?

The state-of-the-art face detection software uses pattern detection technology. No personal data is collected, and no images are stored.

The algorithms decide whether an image is either positive or negative. The application that confirms this state of the image is called a classifier. While detecting a human face, the technology returns to coordinate the locations of the exposed face within a video or an image with a bounding box.

Face Detection - Bounding Box

What are Face Detection Methods?

Experts have classified the face detection method into four categories. The below-given diagram will help you understand more in this regard:

Face Detection Methods

  1. Knowledge-Based: Human knowledge to detect the face, i.e., a face must have a nose, eyes, and a mouth within certain distances and positions with each other.
  2. Feature-Based: This method helps in locating faces by extracting structural features of the face. The idea behind this is to overcome the limits of the instinctive knowledge of faces, and it holds a 94% success rate.
  3. Template-Matching: This method uses parameterized or pre-defined face templates for face detection, establishing a correlation between input images and the templates.
  4. Appearance-Based: This method depends upon a set of face models and is also used in feature extraction for face recognition.

How to run Face Detector Software in Real-Time (Webcam)

If you are done with all the required system settings, you would have to choose suitable software that seems perfect for your business needs. If you are a big business house, you can plan to take advantage of all the advanced features available in proprietary software programs. However, if you have a limited budget, then it is always better to go with the free and open-source face detection software solutions. Here comes the way you can run the face detection software in real-time.

#Import Libraries
#Import Classifier for Face and Eye Detection
#Convert Image to Grayscale
#Give coordinates to detect face and eyes location from ROI
#Webcam setup for Face Detection
#When everything is done, release the capture

Promising Applications of Face Detection Technique

Facebook started inputting automatically generated tag suggestions for all the pictures that are uploaded by the users to the platform. Facebook Company uses a simple face detection algorithm to analyze pixels of images having faces and compares it with the relevant users as if the face matches. Here are some applications that involve promising usage of face detection technology:

Applications of Face Detection Technology

How Face Detection Applications are Useful for Businesses?

Many manufacturing, construction, design, law enforcement, financial, and healthcare industries and businesses are gradually applying facial biometrics to protect their physical and digital possessions.

  1. Payments – FaceTech doesn’t even need customers to use their credit/debit cards for online shopping. MasterCard also introduced a new selfie pay app in 2016 to confirm a payment using their camera. At shopping stores and ATMs, face detection and recognition devices are already installed.
  2. Security and Access – Facial biometrics can also be integrated with physical objects and tools in addition to verifying a payment. Innovative facial security measures are useful for handling sensitive data of a family or organization and keep tight control over whoever is entering their facilities.
  3. Criminal Identification – Face detection applications in combination with Machine Learning (ML) algorithm helps in identifying the suspects from people’s driver’s licenses, merchant licenses, delivery service licenses, and so on.
  4. Advertising – Marketers and advertisers collect and collate the personal data of the masses to target their customers. The best face detection software systems allow companies to recognize specific demographics. For example, a male between the ages of 12 to 21 will get the ad on his mobile screen displaying the latest FIFA game. Many experts assume that cameras could change the face of retail, but only if they correctly identify the customers.
  5. Healthcare – This sector has two advantages of using face detection technology. The first is to secure the patient data by using a unique photo of the patient, instead of usernames and passwords. The second is to identify illnesses by checking out the features of the patients. It helps in slashing long waiting lists and streamlining the appointment process.

Undoubtedly, these applications suggest how useful the face detection technique is to accomplish several jobs and in a variety of fields.

Now, let us check the top-rated free and open source face detection software solutions that most businesses prefer today.

List Of The Best Free and Open Source Face Detection Software

List of The Best Free And Open Source Face Detection Software

Let us compare their features and other aspects in brief to know more about them.

Best Free and Open Source Face Detection Software Comparison Chart

 Best Free And Open Source Face Detection Software Comparison Chart

Let’s have a look at them in detail.

1. OpenBR

OpenBR is a free face detection software that supports the development of open algorithms and reproducible evaluations. The stable version 1.1.0 of the software was released on September 29, 2019. It operates on Windows, Linux, OS X, and Raspbian based operating systems. The project is licensed as per Apache 2.0.


(Source: OpenBR)


  • OpenBR exposes a C++ API that can be embedded into one’s own applications.
  • It is a complete NIST compliant software that evaluates facial recognition, detection, and land-marking.
  • It implements the 4SF2 algorithm to perform face recognition.
  • The software algorithms also work for age estimation and gender estimation.

 2. Flandmark

Flandmark is an open-source C library that implements facial landmark detection in static images. Eydea Recognition Ltd is the company behind providing the face detector to Flandmark. The software works on Windows, Linux, and Mac OS and is licensed as per GNU/GPL version 3. The initial version 1.02 of the software was released on August 10, 2011.


(Source: Flandmark)


  • The Flandmark (version 1.06) can also be used in Python language.
  • Basically, it is written in C, C++, and MATLAB.
  • Each frame is processed separately by the facial landmark software.
  • It uses a structured output classifier that relies on Deformable Part Models (DPM).

3. OpenFaceTracker

As one of the leading facial recognition programs – OpenFaceTracker detects one or several faces on a video or a picture and identifies them through a database. It is an open source face detection software that comes with an lGPLv3 license and stable version 3.0. The invention of the software is inspired by the American TV show ‘Person of Interest.’


(Source: OpenFaceTracker)


  • Can fetch and process real-time images followed by identification, stock, and available print data.
  • It requires Open-API for deployment and can operate on a Windows-based system.
  • The software needs OpenCV3.2 and QT4 to be installed on your computer before installing OpenFaceTracker software.
  • OpenFaceTracker software is developed as a modular library. Hence, it can either enable or disable some part of the software.

4. Open EBTS

Open Biometrics Initiative is an open-source software from ImageWare systems. It is a face detection software for PC that works on 32 and 64-bit Windows and Linux, and now, its beta version is also available. It is written in C++, C, and Java and holds Apache License V2.0.


(Source: OpenEBTS)


  • The initial version of the software was released in April 2010.
  • It is an open specification system that is used by government agencies for the management of biometric data.
  • The software includes two open-source APIs: OpenEBTS API and OpenM1 API.
  • The downloadable source code for the software is managed as per OBI.

5. BioenableTech – iFace

The iFace face recognition time attendance system is a product from Bioenable Technology. It is a multi-biometric identification program that records face and fingerprint time attendance.


(Source: iFace)


  • iFace system is integrated with a 630MHz high-speed multi bio processor.
  • All operations of this system are designed to be performed on the 4.3 TFT touch screen.
  • It includes the face, finger, card, and password related identification methods.
  • EM Card, TCP/IP, Push Data, and Access Control are standard functions of the iFace Face Recognition Time Attendance System.
  • Mifare Contactless Smart Card, HID Prox Card, WiFi, and GPRS are some optional functions of the system.

6. BioenableTech – vFace

Another product by Bioenable Technology – vFace is a Face detection Time and Attendance terminal system that comes with simple access control functionality.        


(Source: vFace)


  • The vFace system is made available in an elegant ergonomic design.
  • Users can be identified with the help of an infra-red optical system even in a poorly lit environment.
  • The system requirements include 3inch TFT touch screen, nine digits user ID, and T9 input.
  • TCP/IP and USB host are communication support associated with this system.
  • This system is applicable in government and civil projects, corporate houses, banks, and security and management sectors.

7. Face++

Face++ can be regarded as a newer version of body outlining. It also accomplishes face comparing and face searching activities to match the faces of the persons with the available database. It offers specific APIs and SDKs powered by up-to-date algorithms.


(Source: Face++)


  • Face_token is used as a unique ID for face detection under this system.
  • The detected faces are stored in the FaceSet.
  • Offline and online, two licensing plans are available as per Mobile SDK, and all SDKs can be tested for free.
  • A free API key is offered to license for a free trial.
  • Integrated C+E solutions, excellent accuracy, robust anti-spoofing technique, and frequent model updating are some other solutions for facial identity verification through Face++ software system.

8. DeepFace

DeepFace is a face detection & face recognition system created by a research group at Facebook that can easily detect and locate human faces in a given image or video. It uses highly reliable deep learning methods with cutting edge technology to obtain a real-time response for real-world applications.


(Source: DeepFace)


  • Instant online face detection and recognition is facilitated by just uploading a photo from the computer or webcam.
  • Fast real-time results are displayed below the face detection, face analysis, face verification, and emotion analysis.
  • Different attributes are facilitated to use by uploading a local image, and analysis is done based on age, gender, head pose, eye status, and skin color.
  • The software facilitates creating a database from faces and search based-on a given image or name. 

We have included one more Face detection Software - FaceFirst for discussion as it is very popular and has great features.


FaceFirst is a powerful tool for facial recognition.  It helps organizations to detect real-time threats, impersonation attempts, and misuse of look alike faces.  FaceFirst empowers companies to create more secure transactions and great customer experiences. FaceFirst uses face recognition and automated video analytics. This software is of immense value for retailers, transportation centers, and event venues. It is also very beneficial for organizations that fight crimes.

Face detection



  • It allows sharing data across unlimited locations.
  • The software can detect faces accurately, even in poor lighting conditions. 
  • Works with camera-enabled service or device
  • Adds face recognition into your existing application
  • Match alerts for faces using mobile push notifications, email, and SMS.
  • Best in class design methodology
  • Two-Minute Deployment process
  • Deployments include automated camera discovery, health monitoring, and server assignments.
  • User-centric design 
  • Solve the operational challenges unique to various companies
  • Query inserted searches the vast databases at a rate of 350 million images per second
  • The proprietary algorithm built with deep machine learning and neural networks
  • Highly configurable and flexible platform
  • Centralized and distributed deployment.

Deep Vision, Ever AI, TrueFace, Clarifi, and Kairos, are other most popular face detection solutions available in the market today.

If you are already using one of the software solutions listed above, you can freely share your reviews here.


It has been ten fruitful years since the very first face detection software for PC was invented that can detect and recognize human faces. Now, a market full of face detection software solutions and programs are available for individual and business uses all over the world.

A report states that in the US alone, over 62 million security cameras are installed using biometric facial recognition, and authentication applications and millions are in people’s pockets as smart gadget-based cameras.

Markets and Markets - a prominent research firm, predicts that the demand for AI-equipped cameras and software will touch $7.76 billion in the coming three years. It will boost the face and fingerprint detection technology in corporate, government, and private sectors, including shopping malls, sports avenues, community gatherings as well.

Face detection technology has great potential to become a predominant one in the future. The probability of errors is merely less when advanced software programs are involved. It securitizes human identities and data within the systems as long as it is kept stored there.

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Sarah Rose Miller
Sarah Rose Miller

She is an IT graduate, a research enthusiast, a  gadget lover and a tech writer. Sarah loves to explore every new innovation in the field of technology to help meeting quests of the readers regarding knowing about new gadget in the market, tech news and publications as well. She is a professional Research and Tech Writer at GoodFirms.co

Responses (3)
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August 28, 2019 10:58

Awesome post, thanks for sharing.

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August 30, 2019 12:36

very helpful for me thank you

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November 13, 2019 04:28

Such an insightful post you have written, thanks for sharing!

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November 13, 2019 04:40

Thanks Kelvin. Glad that you like the article. Do come back for more meaningful insights.

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