Face Detection Basics | Viola Jones Algorithm | Face Uncensored. | S3 E1 | Haar Cascades | ML.

Haar cascades of the Viola Jones Algorithm is the go to place for face detection in machine learning and image processing. So, this particular video will discuss the theory of the Viola Jones algorithm. Today, we will deal with the 4 major components of the algorithm, which are:
1. Haar Features.
2. Integral image.
3. Boosting by Adaboost.
4. Cascading classifiers.

FAQs for the video
1.Is this the beginner level introduction to haar cascades only?
2. Why do we integral image?

FAQs about the channel.
1. Was this a requested series?
2. Subscribe. WHY?
3. Comment. WHY?

Answers for the FAQs on the video.
1.Yes. I have just made sure that the difficult concepts of the algorithm has been explained in the most beginner friendly way as possible. Since these concepts are required to understand the higher order implementation of the algorithm, the video has been designed in the simplest possible way.
2. Actually, integral image helps us find the averages in very short amount of time, which otherwise would have taken a lot of time.

Answers for FAQs on the video.
1. Yes, it was a requested series. My videos are mostly requested video. If you want me to make videos on a particular topic, I would love to do so.
2. It is very common in machine learning students to leave some doubts for later whenever they encounter an advanced or difficult topic. Even though there is nothing bad in that because machine learning concepts are difficult at times, but since those concepts are important, they come to haunt you back. So, if you have notifications for my channel, on, I am pretty sure that some of my videos that I will post will be on the topics that you have missed or are still not clear. The best part of this exercise will be that on some random day you will have an important concept clear without even explicitly going to YouTube to clear those concepts out.
3.Comments help both of us connect inside YouTube. If you post a doubt, I will try to answer that doubt as a reply. If the doubt is good, I will make a video. Yes, I definitely plan to make videos explicitly on complex doubts that are difficult to understand without pictorial demonstrations and a step by step approach. I think this will help the community in the best possible way.
Your comments will also help me know my mistakes and how can we grow as machine learning enthusiasts.