In this article, we will introduce our top 10 Face Detection APIs and how to choose and access the right engine according to your data.
Face Detection API is a technology that enables computers to recognize and locate human faces within an image or video. This technology uses Computer Vision and Machine Learning algorithms to detect and identify faces, and then outputs information about the location, size, and associates characteristics such as age, gender, emotion to it.
Face Detection APIs can be integrated into other applications and systems and can be used for a variety of purposes, such as face recognition, face tracking, and facial expression analysis.
The early pioneers of facial recognition were Woody Bledsoe, Helen Chan Wolf and Charles Bisson. In 1964 and 1965, Bledsoe, Wolf and Bisson began to work with computers to recognize the human face.
It wasn’t until the late 1980s that we saw further progress with the development of Facial Recognition software as a viable biometric for businesses. In 1988, Sirovich and Kirby began applying linear algebra to the problem of facial recognition.
In 1991, Turk and Pentland carried on the work of Sirovich and Kirby by discovering how to detect faces within an image which led to the earliest instances of automatic facial recognition. Face Recognition Grand Challenge (FRGC) was launched in 2006 in order to promote and advance face recognition technology designed to support existing face recognition efforts in the U.S. Government. The FRGC evaluated that the new algorithms were 10 times more accurate than the face recognition algorithms of 2002 and 100 times more accurate than those of 1995, showing the advancements of facial recognition technology over the past decade.
Since the 2010s, Facebook, Apple, Amazon, Google, and other big tech companies developed their own Face detection engines, and face detection is democratized in numerous fields.
api4ai’s Face Detection API can be tailored to specific use cases, easily integrated, and is known for its speed and accuracy. The user-friendly API is cost-effective and provides consistent results, making it an attractive option for businesses and organizations in need of a comprehensive and flexible face detection solution.
Amazon Rekognition can detect faces in images and videos. This section covers non-storage operations for analyzing faces. With Amazon Rekognition, you can get information about where faces are detected in an image or video, facial landmarks such as the position of eyes, and detected emotions (for example, appearing happy or sad). When you provide an image that contains a face, Amazon Rekognition detects the face in the image, analyzes the facial attributes of the face, and then returns a percent confidence score for the face and the facial attributes that are detected in the image.
Clarifai is a leading provider of artificial intelligence for unstructured image, video, and text data. The company helps organizations transform their images, video, and text data into structured data significantly fast and accurately. Their state-of-the-art Face Detection Model can differentiate faces based on only a small number of sample images. Alignment and transformation technology allow you to automatically recognize faces from any angle.
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DeepAI's mission is to accelerate the world's transition to artificial intelligence through offering an A.I. agent that anyone can teach performing a task, in addition to making the latest research and information more accessible through DeepAI. Their face detection API detects and recognizes faces in any image or video frame. By leveraging a deep neural network trained on small, blurry, and shadowy faces of all ages, this service is able to automatically detect faces with a high level of accuracy.
Google Cloud Vision API - a cloud-based Face Detection API provided by Google, offers a comprehensive and reliable solution for Face Detection, which makes it a popular choice for businesses and organizations of all sizes. In addition, The API provides an intuitive and user-friendly interface for developers to access its features and functionality.
Imagga is a computer vision artificial intelligence company. The API features auto-tagging, auto-categorization, face recognition, visual search, content moderation, auto-cropping, color extraction, custom training and ready-to-use models. Available in the Cloud and on On-Premise, it is currently deployed in leading digital asset management solutions and personal cloud platforms and consumer facing apps.
The Azure Face service provides AI algorithms that detect, recognize, and analyze human faces in images. Facial recognition software is important in many different scenarios, such as identity verification, touchless access control, and face blurring for privacy. Face detection is required as a first step in all the other scenarios. The API detects human faces in an image and returns the rectangle coordinates of their locations. It also returns a unique ID that represents the stored face data, which is used in later operations to identify or verify faces.
PicPurify provides a reliable and advanced Face Detection API, offering real-time processing, flexibility, and high-quality results. This API remains the go-to choice for a robust face detection solution.
Sightengine is an Artificial Intelligence company that empowers developers and businesses. Their powerful image and video analysis technology is built on proprietary state-of-the-art Deep Learning systems and is made available through simple and clean APIs. The API’s endpoint can detect and position faces in real-time.
Skybiometry provides a highly accurate and efficient Face Detection API that enables businesses to quickly and easily identify and analyze faces in images and videos. The API is known for its ability to process large volumes of data in real-time, making it a scalable and cost-effective solution for businesses of all sizes.
DeepFace is a deep learning facial recognition system created by a research group at Facebook. It identifies human faces in digital images. The program employs a nine-layer neural network with over 120 million connection weights and was trained on four million images uploaded by Facebook users. DeepFace is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid face recognition framework wrapping state-of-the-art models: VGG-Face, Google FaceNet, OpenFace, Facebook DeepFace, DeepID, ArcFace and Dlib.
Experiments show that human beings have 97.53% accuracy on facial recognition tasks whereas those models already reached and passed that accuracy level.
You can use Face Detection in numerous fields. Here are some examples of common use cases:
Companies and developers from a wide range of industries (Social Media, Retail, Health, Finances, Law, etc.) use Eden AI’s unique API to easily integrate Face Detection tasks in their cloud-based applications, without having to build their own solutions.
Eden AI offers multiple AI APIs on its platform amongst several technologies: Text-to-Speech, Language Detection, Sentiment analysis API, Summarization, Question Answering, Data Anonymization, Speech recognition, and so forth.
We want our users to have access to multiple Face Detection engines and manage them in one place so they can reach high performance, optimize cost and cover all their needs. There are many reasons for using multiple APIs:
You need to set up a provider API that is requested if and only if the main Face Detection API does not perform well (or is down). You can use confidence score returned or other methods to check provider accuracy.
After the testing phase, you will be able to build a mapping of providers performance based on the criteria you have chosen (languages, fields, etc.). Each data that you need to process will then be sent to the best Face Detection API.
You can choose the cheapest Face Detection provider that performs well for your data.
This approach is required if you look for extremely high accuracy. The combination leads to higher costs but allows your AI service to be safe and accurate because Face Detection APIs will validate and invalidate each other for each piece of data.
Eden AI has been made for multiple AI APIs use. Eden AI is the future of AI usage in companies. Eden AI allows you to call multiple AI APIs.
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You can see Eden AI documentation here.
The Eden AI team can help you with your Face Detection integration project. This can be done by :
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