Deep Face Detection

Posted: November 17, 2019 at 6:46 pm

Following from my realization that the haar-based classifier is extremely noisy for face detection, I decided to look into deep-network based face detection methods. I found example code optimized for the jetson to do inference using deep models. Some bugs in the code has made it hard to test, but I’ve fixed enough of those bugs to start an early evaluation at least.

On first blush, the DNN method (using the facenet-120 model) is quite robust, but one of the bugs is a reset of the USB camera’s brightness and focus so that makes evaluation difficult. It does appear that there are very very few false positives. Unfortunately there are quite a lot of false negatives also. It does appear that a complex background is a problem for the DNN face detector as it was for the haar-classifier.

I’m now dumping a bunch of confidence values in a context in which I know there is only one face being detected to get a sense of variance… Then I’ll do a run where I know there will be no faces in the images and see what the variance of confidence is for that case. There is also come DNN-based face detection code in OpenCV that looks to be compatible I’m also trying to figure out.