Facial/Image Recognition APIs

5 Awesome Facial/Image Recognition APIs App Developers Should Know About

Face recognition is not a new feature. But it’s one of the most important use cases of Artificial

Face recognition is not a new feature. But it’s one of the most important use cases of Artificial Intelligence today. Organizations use face and image recognition features to deliver memorable digital user experiences to people. The face recognition feature is quite common nowadays in the form of mobile biometrics. Image recognition features are more prevalent in social media networks.

The market for Face/Image recognition is growing evidently, and is estimated to be close to $10 billion by 2023. With AI powering it, the technology can recognize people just like a human brain can. Back in the days, it wasn’t easy for mobile app developers to implement this feature in web, mobile or desktop apps. But now, there are qualitative APIs that can help them get it done effectively.

Here are a few popular ones that app developers should try out at least once.

Amazon Rekognition

Amazon Rekognition is an image/video recognition tool that can analyze image and video files in Amazon S3. The API is powered by deep learning technology developed and owned by Amazon.

Key features include:

  • Face recognition in videos and images
  • Facial analysis to determine emotion, age range etc.
  • Text detection in images
  • Unsafe content detection
  • Object/activity detection

Kairos

Kairos is another popular face recognition API that utilizes a potent combination of computer vision and deep learning to recognize faces in videos, images, and in the real world.

Key features include:

  • Face recognition and identification
  • Gender and age detection
  • Multi-face detection
  • Diversity recognition

Microsoft Computer Vision API

A widely used API developed by Microsoft, the Computer Vision API can process visual data in real-time and possesses machine-assisted image moderation capabilities. Developers use this API to implement a feature that lets the application identify people who were previously tagged in images.

Key features include:

  • Image analysis
  • Real-time video analysis
  • Text detection in images
  • Read handwritten text in real-world environments
  • Recognize over 200,000 celebrities and landmarks

Watson Visual Recognition API

The Watson Visual Recognition API deserves to be on this list as it’s a favorite for a lot of developer communities in the web. The API enables tagging, classifying, and searching visual content using deep learning algorithms. Another great feature is that the Watson Visual Recognition API can be integrated with Core ML to build complex iOS apps with computer vision and analytics capabilities.

Key features include:

  • Analysis of object, face, explicit content etc.
  • Pre-defined image analysis models
  • Creation of custom models that can be trained

Google Cloud Vision

Google Cloud Vision features a number of pre-trained models for impressively accurate image recognition and analysis. The API allows developers to build use case-based custom models using AutoML Vision.

Key features include:

  • Wide array of pre-trained models ranging from transportation to wildlife
  • ML Kit integration for Android iOS app development
  • Handwriting, face, and landmark detection
  • Explicit content detection
  • Sentiment analysis

Conclusion

Even with the right tools and APIs, implementing face and image recognition features in apps is a complex process. In addition, this also requires trained AI/ML models. To conclude, all this and more can be done only if the developer has great expertise in leveraging AI and app development. AOT has proven expertise in developing complex AI-driven mobile apps for Android and iOS platforms. If you are planning to utilize a next-gen app with facial/image recognition features, we can help. Get in touch with us to check out our track record.

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