But First let me take a #SELFIE: Facial Recognition with Deep Learning

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First of all, let me ask a question; how many of you take selfies? I think the answer is quite simple and it is obviously a big ‘YES’. Well then let me rephrase it; how many of you take selfies only after the camera detects your face? Now something interesting is coming. You know how it detects your face, your age, your gender and sometimes even your name.

Let me take one more example. Well, I am pretty sure that everyone out there must be using ‘tag your friend’ option on Facebook. Have you ever noticed that typing their names individually is not required, as soon as you upload a photo, Facebook tags everyone for you like magic.

Is this really a magic? No, not at all. This is technology. This is Facial Recognition.

Now let us talk about Facial Recognition. According to Wikipedia, A facial recognition system is a computer application capable of identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a face database. It is typically used in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems. Recently, it has also become popular as a commercial identification and marketing tool.

However, human facial expressions change so frequently that recognition accuracy of most traditional approaches largely depend on feature extraction. Here, deep learning comes into picture, which intends to simulate the organizational structure of human brain's nerve and combine low-level features to form a more abstract level. And these deep learning techniques have been used over images displaying the following facial emotions: happiness, sadness, anger, surprise, disgust, and fear.

Now let us discuss few applications of facial expressions that are widely being used around us.
  •       Payments
  •       Access and security
  •       Criminal identification
  •       Advertising
  •       Healthcare

To verify payments, grant access and improve existing security systems our physical is necessary. That time is not so far when instead of unlocking the door with a key, we will do it with our face. As per a market analysis, by 2022, the global facial recognition technology market is projected to generate an estimated $9.6 billion in revenue with a compound annual growth rate (CAGR) of 21.3 percent.

For more details contact us.
Name: Amelia Smith
Contact:machinelearning@enggconferences.com;
worldmachinelearning@enggconferences.com
Website: https://machinelearning.conferenceseries.com/

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