Archive | Facial Landmarks

Optimizing dlib shape predictor accuracy with find_min_global

In this tutorial you will learn how to use dlib’s find_min_global function to optimize the options and hyperparameters to dlib’s shape predictor, yielding a more accurate model. A few weeks ago I published a two-part series on using dlib to train custom shape predictors: Part one: Training a custom dlib shape predictor Part two: Tuning […]

Continue Reading 2

Tuning dlib shape predictor hyperparameters to balance speed, accuracy, and model size

In this tutorial, you will learn how to optimally tune dlib’s shape predictor hyperparameters and options to obtain a shape predictor that balances speed, accuracy, and model size. Today is part two in our two-part series on training custom shape predictors with dlib: Part #1: Training custom dlib shape predictors (last week’s tutorial) Part #2: Tuning […]

Continue Reading 2

Raspberry Pi: Facial landmarks + drowsiness detection with OpenCV and dlib

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 and potentially falling asleep at the wheel. The driver drowsiness detector project was inspired by […]

Continue Reading 234

Eye blink detection with OpenCV, Python, and dlib

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 in video streams using facial landmarks and OpenCV. To build our blink detector, we’ll be […]

Continue Reading 289

Real-time facial landmark detection with OpenCV, Python, and dlib

Over the past few weeks we have been discussing facial landmarks and the role they play in computer vision and image processing. We’ve started off by learning how to detect facial landmarks in an image. We then discovered how to label and annotate each of the facial regions, such as eyes, eyebrows, nose, mouth, and jawline. Today […]

Continue Reading 151

Detect eyes, nose, lips, and jaw with dlib, OpenCV, and Python

Today’s blog post is part three in our current series on facial landmark detection and their applications to computer vision and image processing. Two weeks ago I demonstrated how to install the dlib library which we are using for facial landmark detection. Then, last week I discussed how to use dlib to actually detect facial landmarks in […]

Continue Reading 208
[email]
[email]