Detection, Landmarking

Detect faces within a frame, generate key points on the face, and begin tracking dwell time and session time. Pass that detection into our neural networks for our demographics.

Neural Network

Once we detect and landmark, the detection is passed to our neural network to generate a hierarchy of features, to compare to our existing model of what our demographics should look like.

Generate Demographics

From there, we generate age, gender, and emotion for detected person and push these metrics to the dashboard, trigger webhooks, and store in our database.

Accuracy and Metrics

Below are updated statistical analysis of the accuracy of our data points. We improve these daily and will grow the types of metrics we gather as we further develop our technology platform.

Metrics Accuracy (%)
Happy 80.5
Angry 83.3
Surprised 91.1
Fear 82.6
Sad 78.1
Disgust 98.5
Calm 80.8
Metrics Accuracy (%)
Male 91.3
Female 91.3
Age +/- 10 years
View +/- 5 degrees (91.3%)
Dwell Time +/- 100 ms

Uniqueness and Occlusion Algorithms

We use a combination of complex tracking and detection algorithms to maintain a person's session across the screen.

Our complex algorithms can handle occlusions, obstructions, and lost detections, to maintain the uniqueness of a person over the session.

A user's "session" is considered from the time the face is first detected, till an interval of time that the face can no longer be detected.

Low Latency

Our Computer Vision algorithms allow for low latency implementations, on low cost hardware solutions on site, or remotely.

We've optimized our detections to process faces as low as 2 milliseconds per face at a distance of approximately 25-30 feet.


Our Computer Vision technology can be applied to any number of cameras with short and long-range vision.

The quality of our metrics are independent of the range, and purely based on the pixel dimensions of the detections.

Our testing range and minimum detection size is 30x30 pixels, at a distance of 25 feet, and can be extended with higher resolution cameras.

Multi-Platform Support

Our libraries were designed to be easily deployable and support both OpenCV and OpenCL integrations.

On how to get started with our SDKs, please contact us.