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Age Recognition

  • Accurate age estimation
  • Plug and play solution
  • Start for free

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Get valuable insights into your audience and learn more about their profiles

Detect and measure facial features like age, gender, and emotional expressions such as happiness, surprise, sadness, disgust, anger, and fear.

DeepSight Toolkit

  • Get started quick and easy
  • No need for hard coding
  • Real-time analysis
  • Get specific age estimation

DeepSight SDK

  • Software Development Kit
  • Build your own solution
  • C++ expertise needed
  • Works offline (one-time internet connection)
  • Age Estimation


  • Audience Analytics Solution
  • Ready reports connected to the Toolkit
  • Plug & Play solution
  • No need to program
  • Get Age Range

Get to know your customers

Target and deliver tailored content to individuals based on their demographic profiles

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We are using and heavily promoting Sightcorp’s Toolkit because of its stability, accuracy and very easy installation and hardware configuration. The real-time aggregated data is immediately accessible through the reporting dashboard, which enables us to scale with ease.

─ S. Ahmedov, CEO OmniChannel


Age Recognition

What is age recognition?

Age recognition is the estimation of people’s age based on biometric features, more specifically their facial features. The software determines age using an algorithm trained on a large database of different human faces. The technology tracks multiple facial features via a camera sensor and gives an estimate on the age of each individual.

Why is age recognition important?

Information about people’s age can be used for different purposes such as targeting, advertising, audience analytics and many more. With automatic age estimation, our clients can easily manipulate and deliver their content to the right age group at the right time. Also, clients can gather valuable insights into their converted customers and viewing audience.

Can you determine the exact age?

Our technology can recognize age within 10-year range groups (0-9, 10-19, 20-29, 30-39, 40-59, 60+). These age groups can be very useful for tailoring different content for instance to young adults vs. seniors. Knowing the exact age of each person is not always essential for effective targeting.

How accurate is your age recognition?

Our software can estimate age with accuracy up to +/- 5 years. The highest accuracy can be achieved by creating a suitable scenario for the software such as placing the camera at eye level of individuals together with optimal lighting conditions.

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Technical Specifications

The table below shows how FaceMatch SDK performs on the Labelled Faces in the Wild (LFW) dataset:

FPRTPRThreshold (Inverse of distance)
0.10.99900 ±0.002130.55448
0.010.99667 ±0.005370.59791
0.0010.99367 ±0.006050.62989

FPR = False Positive Rate
TPR = True Positive Rate

These results are an indication only and are based on the specific dataset Labelled Faces in the Wild. Customers can expect similar performance, with possible variations due to hardware and the availability of annotated data.