face-detection

I'm writing a HttpHandler in C# which serves resized images and blah blah blah... No troubles, we have millions of handlers to use as reference. The problem is that I have pictures of my users taken with "traditional" sizes, as 4:3 and 16:9. But this handler will need to serve the picture in a Photo ID size (4cm by 3cm) and obviously has need of cropping around the user face . The faces positions vary a lot (aren't always at the picture center). So, what kind of algorithm I could use to detect the face center and then crop the image around this point? Muhammad Hasan Khan You can use

Currently I am trying to convert Camera2.Face to actual view's rect in order to draw circle over the face detected by the Camera2 API. I am able to get number of faces and its data into Callback by below code: private CameraCaptureSession.CaptureCallback mCaptureCallback = new CameraCaptureSession.CaptureCallback() { private void process(CaptureResult result) { Integer mode = result.get(CaptureResult.STATISTICS_FACE_DETECT_MODE); Face [] faces = result.get(CaptureResult.STATISTICS_FACES); if(faces != null && mode != null) Log.e("tag", "faces : " + faces.length + " , mode : " + mode ); }

I need some help on LBP based face detection and that is why I am writing this. I have the following questions related to face detection implemented on OpenCV: In lbpCascade_frontal_face.xml (this is from opencv): what is internalNodes, leafValues, tree,features etc? I know they are used in the algorithm . But I do not understand the meaning of each one of them. For example, why we take a particular feature and not the other for a particular stage? how we are deciding which feature/ node to choose? What is feature values in the LBP_frontal_face_classifier.xml? I know they are a vector of 4

Wanted to ask if there was any kind of face detection scheme suitable for video that would require minimal training time ideally about a few days rather than weeks like the Viola-Jones. I have read about LBP but it requires a huge set of training samples too but not sure how long it takes. Does training an LBP consume as much time as the Viola - Jones method with a similar number of training set ?. I will be implementing this on a microprocessor like raspberry pi running on a linux OS. Will want to implement it on C for speed as I want it to be able to detect images in a 10fps - 20fps video

Is there a library for detecting faces that have been rotated in the image plane? Or is there some way in which I could use a cascade for upright face detection with opencv to do it? Here's a simple one I wrote with Python cv2 It's not the most efficient thing, and it uses the naive way suggested by etarion, but it works fairly well for just normal head tilting (It detect anything from -40 to 40 head tilt, which is roughly as much as you can tilt your head staying upright. import cv2 from math import sin, cos, radians camera = cv2.VideoCapture(0) face = cv2.CascadeClassifier("haarcascade

Does anybody know of a good way to do face detection in PHP? I came across some code here that claims to do this, but I can't seem to get it to work properly. I'd like to make this work (even though it will be slow) and any help you can give me would be really appreciated. Here's the code from the link: <?php // as published by the Free Software Foundation; either version 2 // of the License, or (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS

How can I do face detection in realtime just as "Camera" does? I noticed that AVCaptureStillImageOutput is deprecated after 10.0, so I use AVCapturePhotoOutput instead. However, I found that the image I saved for facial detection is not so satisfied? Any ideas? UPDATE After giving a try of @Shravya Boggarapu mentioned. Currently, I use AVCaptureMetadataOutput to detect the face without CIFaceDetector . It works as expected. However, when I'm trying to draw bounds of the face, it seems mislocated. Any idea? let metaDataOutput = AVCaptureMetadataOutput() captureSession.sessionPreset =