# Tag Info

## Hot answers tagged facial-recognition

Accepted

### What is the formula used to calculate the loss in the FaceNet model?

The loss function used is the triplet loss function. Let me explain it part by part. Notation The $f^a_i$ means the anchor input image. The $f^p_i$ means the <...
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### How Euclidean distance algorithm calculate two different face images are match or not match in face recognition?

Simply put, Euclidean distance measures how far away two items are (see Neil Slater's comment). In order to apply this to a pattern recognition task, you will need to convert the items to compare (in ...
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### Is algorithmic bias due to the training dataset used?

Just to add to what has already been said in @BlueMoon93's answer: Algorithmic bias is the bias built into the algorithm. Now for the long answer: As stated by the so called No free lunch theorem: ...

### Is algorithmic bias due to the training dataset used?

As the name implies, algorithmic bias is related with the used algorithm. Due to the way it was programmed or devised, the algorithm will be biased in some of its samples. From Communications of the ...
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### Is it possible to fool a facial recognition algorithm?

Facial recognition works by essentially turning your face into a point cloud, recognizing eyes, cheeks, nose, mouth, etc. Unfortunately it doesn't look at the top of your head (hair is very hard to ...

### Which AI methods are most appropriate for login face recognition?

One of the methods which is quite fast and easy to implement. You can do Principal Component Analysis (PCA) based face recognition. You can go through this paper for the theory behind it. For an ...
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### What is the minimum video resolution I need to identify anyone with facial recognition?

On page 2 of Axis' web page Identification and Recognition there is an estimate of the minimum number of pixels needed for identification, recognition and detection.
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### How to identify if 2 faces contain the same person?

The topic of your problem is person re-identification. You can check here.
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### Is it possible to do face recognition with just the eyes?

Yes, it must be possible as retina scanners have been used as a method of personal identification for some time. The difference is, if you have a retinal scanner you are probably controlling the focal ...
• 131
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### How does ARKit's Facial Tracking work?

Facial classification and tracking is easier compared to tracking any other motion. This is due to the fact that the face have a large number of easily identifiable features. Facial tracking is an ...
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### Facial recognition and classifying unknowns with neural networks

Summary It is true that neural networks are inherently not good at classifying 'unknowns' because they tend to overfit to the data that they have been trained on, if the underlying structure of the ...
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### Viola Jones Algorithm

An introduction to the Haar features is provided in the youTube video. The video indicates the VJ face detector leverages a selected combination of Haar features (convolutional kernels) to detect ...
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### How long it takes to train face recognition deep neural network? (rough estimation)

Training time depends on a lot of parameters. Some of them are: Size of each image (resolution) Color/Monochrome image (color image has 3 times data if you consider RGB image) Like you mentioned on ...
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### Detailed explaination of Facenet Model for face recogniton?

Facenet is a Siamese network. It's basic architecture is this: The input(a face) is fed through a deep convolutional neural network and also a fully connected layer at the end. The fully connected ...
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### How to identify the face of a certain customer in a grocery store?

You might consider pre-training a CNN on a large dataset. The CNN should be structured such that you input 2 different images and the CNN predicts whether or not they are the same person. Your dataset ...

### How to identify if 2 faces contain the same person?

You can try using something called as a Siamese network if you are willing to train the network on your own using something called as triplet loss(if you have lots of face images). Another approach ...
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### How to tackle the human error made in labeling datasets for classification tasks like facial expression recognition?

In general the only way to deal with this is by quantifying these labeling mistakes in the output of the model, since the model will learn for them. And in many cases these are not really mistakes, ...
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### What is the minimum video resolution I need to identify anyone with facial recognition?

This is a pretty standard minimum "quality" (better said resolution in pixels between the eyes) needed for a facial recognition system: Ensure that the image contains a frontal view of the ...
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### Why are the landmark retrieval and facial recognition literature so divergent?

Landmark retrieval has photographs of landmarks that you need to find out. Consider the degrees of freedom for this, the landmarks can many different colours (more than humans' faces) and also the ...
1 vote

### Is it possible to do face recognition with just the eyes?

The two main eye biometrics are iris recognition and retina recognition (aka retinal scan). These are not going to work from an ordinary photo of someone's face. I have used iris recognition at ...
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1 vote

### Does anyone know of a model for comparing the eyes of people in two images to see if they match?

The model you are looking for is probably a Siamese Neural Networks. It's very used for Biometrics. This kind of model learns to extract relevant and features (For example, facial metrics) that are ...
1 vote

### What is 3D face recognition? and how we can check liveness of a face image?

1. What is typically meant by 3D-face recognition? We are usually extracting the face encoding from 2D-images, right? Yes. The goal is to reconstruct the three-dimensional shape, as well as the ...
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1 vote
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### How is the percentage or the probablity calculated using Loss function in Facenet Model?

The facenet model is just the head of the model. The architecture is similar to the enocdr part of an autoencoder, but it uses supervised learning instead of unsupervised learning. The network is ...
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1 vote

### How long it takes to train face recognition deep neural network? (rough estimation)

YELP Dataset (200k images) used to take 5 hr for training to identify Five (5) classes on GPU - Nvidia 1080 Ti with 11 GB RAM. So I guess in your case it will take days. Again it will depend on the ...
1 vote

### How to identify whether images contain driver's licenses or ID cards

Why not make a detector/classifier to look for the text "Drivers Licence" or some very generic keywords related to license? As you mentioned images of people may be present in any sort of documents. ...
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1 vote

### Facial Recognition + Database + Compare & Identify - is it complicated?

Depending on the level of accuracy/speed you want your system to have, you could try using an existing python API. First thing I found on google, the README looks adapted to your project. Otherwise ...
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### How can we use data augmentation for creating data set for face recognition and will the inverted faces on augmented images detected?

This is the purpose of rotational augmentation. In fact you should augment your images at different angle as well than just inverting it. This will make your model angle agnostic.
1 vote
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### Can I recognize the faces of people around the world?

I thought it might be a helpful place to start: https://en.wikipedia.org/wiki/Google_Street_View_privacy_concerns The wiki is well cited, so should lead to some useful tidbits. They break it down by ...
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1 vote

### Viola Jones Algorithm

I have once tried Viola Jones Algorithm to do that, it does not capture the subtle differences in the direction of facial segments which are important to detect emotion. Features like HOG (Available ...
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1 vote
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### Searching an AI to recognize and locate persons in a factory

I am definitely not the most qualified person in order to answer this question, but I might be able to give you a couple of buzz words to go and do some more research on your own. A convolutional ...

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