Our face detection technology
goCount uses camera mounted on a screen, to detect faces and estimate their dwell time.
This approach requires really good face detector, that provides:
- stable detection in unrestricted environment (various lighting conditions, face pose and etc.)
- stable detection at a distance of 10 meters from the camera, to count all viewers
- low CPU usage, to host both goCount and content management software (e.g. Scala) on the same machine
- high accuracy
We’ve tested several open source and commercial solutions and no one met all the requirements.
That is why we’ve developed our own face detection, which is:
- stable to lighting conditions and face pose
- highly accurate (false alarm rate is about 3%)
- capturing faces at a distance of 0-10 meters from camera
- requires less CPU
goCount vs. OpenCV
Let’s see how goCount and OpenCV handle the same video.
Face size range: 24x24px – 480x480px, which is equivalent to 0-5 meters distance
Machine: Intel Core i7-4500U 1.8GHz
|Frame processing time||60 ms||30 ms|
|face tracking||not available||available|
|age and gender detection||not available||available|
As you can see, our face detection is faster and more accurate.