Face Applications

In last week’s blog post you learned how to perform Face recognition with Python, OpenCV, and deep learning. But as I hinted at in the post, in order to perform face recognition on the Raspberry Pi you first need to…

In today’s blog post you are going to learn how to perform face recognition in both images and video streams using: OpenCV Python Deep learning As we’ll see, the deep learning-based facial embeddings we’ll be using here today are both…

In the next couple of blog posts we are going to train a computer vision + deep learning model to perform facial recognition… …but before we can train our model to recognize faces in images and video streams we first…

Back in September 2017, Davis King released v19.7 of dlib — and inside the release notes you’ll find a short, inconspicuous bullet point on dlib’s new 5-point facial landmark detector: Added a 5 point face landmarking model that is over…

Today I’m going to share a little known secret with you regarding the OpenCV library: You can perform fast, accurate face detection with OpenCV using a pre-trained deep learning face detector model shipped with the library. You may already know…

Today’s blog post is the long-awaited tutorial on real-time drowsiness detection on the Raspberry Pi! Back in May I wrote a (laptop-based) drowsiness detector that can be used to detect if the driver of a motor vehicle was getting tired…

Continuing our series of blog posts on facial landmarks, today we are going to discuss face alignment, the process of: Identifying the geometric structure of faces in digital images. Attempting to obtain a canonical alignment of the face based on…

My Uncle John is a long haul tractor trailer truck driver. For each new assignment, he picks his load up from a local company early in the morning and then sets off on a lengthy, enduring cross-country trek across the United…

In last week’s blog post, I demonstrated how to perform facial landmark detection in real-time in video streams. Today, we are going to build upon this knowledge and develop a computer vision application that is capable of detecting and counting blinks…