What is gender recognition?
Gender recognition, in the context of facial analysis, refers to the process of using artificial intelligence technology to identify whether a facial image is more likely to belong to a male or to a female.
Using deep learning methods, facial analysis software can recognize gender based on images or videos of faces with remarkable accuracy (more on this below).
How is gender recognition used in practice?
Gender recognition is useful in a variety of contexts, ranging from anonymous audience analytics to identity verification and access control.
With audience analytics, retail store owners, digital screen owners and advertisers want to know the demographics of the people they are communicating with. When they know the gender distribution of their audience, they can tailor their messaging accordingly, and thereby improve engagement, increase ROI, and enhance the customer experience.
Here is an example of how gender recognition combines with real-time audience analysis to provide tailored content to prospective customers:
Sightcorp’s gender recognition software
At Sightcorp, our gender recognition software forms part of our face analysis software (illustrated in the gif/video above), and is 100% based on deep learning. The accuracy of gender recognition in our DeepSight products is 93.8% across male and female genders and across all ethnicities.
The table above compares the accuracy of our gender recognition software in DeepSight and its predecessor CrowdSight. The increase in accuracy is largely due to the introduction of deep learning.
Gender recognition combined with other elements of face analysis
Since our face analysis software combines gender recognition with age recognition, head pose detection, attention time, and smile detection, it is a perfect fit for audience analysis in the retail and digital signage space.