How does Haar Cascade detect face?

So what is Haar Cascade? It is an Object Detection Algorithm used to identify faces in an image or a real time video. The algorithm uses edge or line detection features proposed by Viola and Jones in their research paper “Rapid Object Detection using a Boosted Cascade of Simple Features” published in 2001.

Can Haar Cascade detect multiple faces?

Some of them have a single side of the face visible, so the Haar model did not detect anything. Some of them have multiple faces detected as there more than one person in the images. In some of them, the model detects a tie as a face, or it detects only one eye in one of them.

How accurate are Haar Cascades?

By using Equation (3) Accuracy is obtained for the Haar cascade is 96.24% and for LBP classifier 94.74%.

Is Haar Cascade CNN?

Haar Cascade is an algorithm that is used to detect a face quickly and in real-time. At the same time, CNN utilizes the convolution process by moving a convolution (filter) kernel of a specific size to the next image from the result of multiplying the image with the filter used.

Why use Haar Cascade algorithm is best?

Some Haar cascade benefits are that they’re very fast at computing Haar-like features due to the use of integral images (also called summed area tables). They are also very efficient for feature selection through the use of the AdaBoost algorithm.

How do you use Haar Cascade?

Haar Cascade is a machine learning-based approach where a lot of positive and negative images are used to train the classifier.

  1. Positive images – These images contain the images which we want our classifier to identify.
  2. Negative Images – Images of everything else, which do not contain the object we want to detect.

What is Haar cascade classifier?

Haar Cascade is a machine learning-based approach where a lot of positive and negative images are used to train the classifier. Positive images – These images contain the images which we want our classifier to identify. Negative Images – Images of everything else, which do not contain the object we want to detect.

Which machine learning algorithm is used in face recognition?

Facial detection via the Viola-Jones algorithm is a com- mon method used due to its high detection rate and fast pro- cessing speed. The algorithm can be summed up in four steps: feature selection, feature evaluation, feature learning to create a classifier, and cascading classifiers.

What is better than Haar Cascade?

An LBP cascade can be trained to perform similarly (or better) than the Haar cascade, but out of the box, the Haar cascade is about 3x slower, and depending on your data, about 1-2% better at accurately detecting the location of a face.