Active Appearance Model face for ios - ios

I am using OpenCV to develop an iPhone application, and I am using it to detect faces. Rather than detect the face as a whole, I would like to detect each of the smaller facial features (eyes, nose, ears, lips, etc.). Actually,I want to do something like this link
How to use aam-opencv for iOS?
I searched on internet and I found this link
But I don't know how to apply this on iOS.
Please, can you help me about facial expression recognition?

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Apple Vision Framework Identify face

Is it possible in the Apple Vision Framework to compare faces and recognise if that person is in a picture compared to a reference image of that person?
Something like Facebook Face recognition.
Thomas
From the Vision Framework Documentation:
The Vision framework performs face and face landmark detection, text
detection, barcode recognition, image registration, and general
feature tracking. Vision also allows the use of custom Core ML models
for tasks like classification or object detection.
So, no, the Vision Framework does not provide face recognition, only face detection.
There are approaches out there to recognize faces. Here is an example of face recognition in an AR app:
https://github.com/NovatecConsulting/FaceRecognition-in-ARKit
They trained a model that can detect like 100 persons, but you have to retrain it for every new person you want to recognize. Unfortunately, you can not just give two images in and have the faces compared.
According to Face Detection vs Face Recognition article:
Face detection just means that a system is able to identify that there is a human face present in an image or video. For example, Face Detection can be used to auto focus functionality for cameras.
Face recognition describes a biometric technology that goes far beyond a way when just a human face is detected. It actually attempts to establish whose face it is.
But...
In a case you need an Augmented Reality app, like Facebook's FaceApp, the answer is:
Yes, you can create an app similar to FaceApp using ARKit.
Because you need just a simple form of Face Recognition what is accessible via ARKit or RealityKit framework. You do not even need to create a .mlmodel like you do using Vision and CoreML frameworks.
All you need is a device with a front camera, allowing you detect up to three faces at a time using ARKit 3.0 or RealityKit 1.0. Look at the following Swift code how you can do it to get ARFaceAnchor when a face has detected.
And additionally, if you wanna use reference images for simple face detection – you need to put several reference images in Xcode's .arresourcegroup folder and use the following Swift code as additional condition to get a ARImageAnchor (in the center of a detected image).

What is the difference between Face Detection and Face Tracking in iOS perspective

May be this sounds like a stupid one, but i really curious to know that, what is the difference between "Face Detection and Face Tracking" in iOS perspective? And in what case or which kind of situation should i use the two of them.
First of all you known about Vision Framework!!
Following this link:- https://developer.apple.com/documentation/vision
Vision — a framework to apply high-performance image analysis and computer vision techniques to identify faces, detect features, and classify scenes in images and video.
Face detection. Detects all faces on selected photo.
Face landmarks. An image analysis that finds facial features (such as
the eyes and mouth) in an image.
Object tracking. Track any object using camera.
Among a lot of new APIs there is the Vision Framework which helps with detection of faces, face features, object tracking and others.
Hope will helpful to you!!
The Face Detection is done by the Apple Framework CoreImage Framework. Available since iOS 5+, (besides the Vision Framework).
You can use the https://developer.apple.com/documentation/coreimage/cidetector
CIDetector to detect faces.
Face detection will return face landmarks such as eyes, lips, nose. This frames can be used to modify the faces with image processing.
You can also use the faces found, and use it with a third party Face Recognitions API's to recognize faces (Microsoft face API) .
Face Tracking
Can be used to track the real time location of face features, and possible apply filters to it (snapchat, etc).

Is that possible to get facial expression information like animojis via CoreML or ARkit?

As Apple shown yesterday, the Animoji is amazingly retarget human facial movement to emojis,
so is it possible for us to use something like the picture below via CoreML or ARkit?

Detect an object and take photo

You might have seen that option in one of the samsung phone that when a person smile it take the photo. So it somehow detects the smile and the click the photo automatically.I'm trying to create the similar thing on iOS that lets say if the camera detects a chair it clicks the photo.I've searched around and what I found is that there is a library called OpenCV but I'm not sure it'll work with iOS or not. Plus there is a concept of CoreImage in iOS which has something to do with deep understanding of the image. So any idea about this?
openCV For iOS
For detection you can use openCV framework in iOS and the native detection methods. In my application i am using openCV rectangle detection and the scenario is: after taken picture openCV detects rectangle on the image and then makes lines on detected shape, also it can crop the image with basic functionality and as perspective correction.
options: Face Detection, Shape Detection
Native way:
iOS provides us real time detection there are many tutorials how to use them i will link at the end of the thread. Native way also provides us face detection, shape detection and perspective correction.
Coclusion:
Choice is up to you but i prefer native way. remember openCV is written in C++ if you are using swift language you can import openCV in your project and then connect swift to objective-C to call openCV. Using Bridging Headers
Tutorials:
Medium Link 1
Medium Link 2
Toptal Tutorial
How to use OPENCV in iOS

Motion Sensing by Camera in iOS

I am working on an app in iOS that will occur an event if camera detects some changes in image or we can say motion in image. Here I am not asking about face recognition or a particular colored image motion, And I got all result for OpenCV when I searched, And I also found that we can achieve this by using gyroscope and accelerometer both , but how??
I am beginner in iOS.So my question is , Is there any framework or any easy way to detect motion or motion sensing by camera.And How to achieve?
For Example if I move my hand before camera then it will show some message or alert.
And plz give me some useful and easy to understand links about this.
Thanx
If all you want is some kind of crude motion detection, my open source GPUImage framework has a GPUImageMotionDetector within it.
This admittedly simple motion detector does frame-to-frame comparisons, based on a low-pass filter, and can identify the number of pixels that have changed between frames and the centroid of the changed area. It operates on live video and I know some people who've used it for motion activation of functions in their iOS applications.
Because it relies on pixel differences and not optical flow or feature matching, it can be prone to false positives and can't track discrete objects as they move in a frame. However, if all you need is basic motion sensing, this is pretty easy to drop into your application. Look at the FilterShowcase example to see how it works in practice.
I don't exactly understand what you mean here:
Here I am not asking about face recognition or a particular colored
image motion, because I got all result for OpenCV when I searched
But I would suggest to go for opencv as you can use opencv in IOS. Here is a good link which helps you to setup opencv in ios.
There are lot of opencv motion detection codes online and here is one among them, which you can make use of.
You need to convert the UIImage ( image type in IOS ) to cv::Mat or IplImage and pass it to the opencv algorithms. You can convert using this link or this.

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