Age detection automatically estimates a person’s age from an image or video. The age detector model is built based on a large number of pictures of different ages as a training dataset.
The age detection technology uses computer vision to analyze the facial attributes showing a person’s age and estimates their most probable age.
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How Does It Work?
The model identifies all the faces in the image and displays the estimated age for each person based on the facial attributes. The model generates a list containing all the faces in the image, showing their corresponding age with probabilities.
Input
The input is an image.
Output
Output is a list of dictionaries, including the coordinates of all the faces and the detection probabilities. The location of the detected face is in the form of the top-left and bottom-right pixel coordinates of the frame. In the corresponding dictionary of a face, the value for age and the probability of estimation are presented.
For example
[
{
"probability": 0.99,
"rectangle": {
"left": 89.36750197336077,
"top": 57.552113214756055,
"right": 293.84930589000385,
"bottom": 350.8455882774045
},
"age": {
"value": 27,
"probability": 0.78
}
}
]
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Technologies Used in SmartClick’s Age Detector
Age Detector Use Cases
Personalized Customer Experience
With our age detector, you can get actionable insights into your customers’ age range to understand their needs and interests. This information will help you deliver a more enhanced customer experience and drive more sales.
Better Ad Targeting
Getting detailed metrics on your audience’s age groups may be used for more effective ad retargeting. Based on these data, you can segment your customers according to their age group to target the right people with more relevant content.
Content Moderation
Our age estimation technology can support websites and platforms to automatically control access to age-restricted content, such as gaming, gambling, violence, adult content, etc. The system may prevent minors from viewing inappropriate content, ensuring a safer online experience for them.
Content Recommendation Systems
Knowing your customers’ age range can be essential for providing personalized content recommendations. You can use these data to show products and services that users will find most relevant to engage with.
Surveillance Monitoring
Age estimation technology has many use cases related to surveillance monitoring. It comes as a scalable solution for detecting human age across camera streams in real time and controlling access to facilities by age group.
FAQ
Which algorithm is used for age detection?
Our age detection API is based on a regression model algorithm using deep learning techniques.
How do you classify age?
A deep learning model is trained on a large database with the faces of humans and the age they are at the time when the picture was taken. Using a regression technique, the model learns to predict age.
What are the 4 types of age?
The age of a human being is divided into four categories:
- Chronological age is determined by the actual amount of time a person has lived from birth to a given date.
- Appearance age refers to the age a person actually looks.
- Biological age is measured by a human’s physical and mental functions and the state of the body.
- Psychological age describes the age an individual feels and behaves.
How long does it take to recognize age from a picture?
One of the benefits of our age estimation technology is that the speed of the model is near real time.
