face-recognition

i'm trying to convert a pre-trained frozen .pb based on Inception ResNet i got from David Sandbergs Github with the Tensorflow Lite Converter on Ubuntu using the following command: /home/nils/.local/bin/tflite_convert --output_file=/home/nils/Documents/frozen.tflite --graph_def_file=/home/nils/Documents/20180402-114759/20180402-114759.pb --input_arrays=input --output_arrays=embeddings --input_shapes=1,160,160,3 However, i get the following error: 2018-12-03 15:03:16.807431: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not

Is it possible to detect eye in the video mode in MATLAB? I am trying to detect the eye and make some predictions based on the movement of the eye. But am not sure on how to do that. Can someone help me in how to start about that? Thanks in advance. You could take a look at this set of functions on The MathWorks File Exchange: Fast Eyetracking by Peter Aldrian . Quoting from the description of the post (to give a little more detail here): This project handles with the question how to extract fixed feature points from a given face in a real time environment. It is based on the idea, that a face

I have successfully detected a face out of an image having other things in background using OpenCv . Now I need to extract just the detected part (i.e. face) and convert it into some image format like jpeg or gif to make a face database to use for my neural net training. How can I do this? Once you detect the faces, you get opposite corners of a rectangle, which is used to draw rectangles around the face. Now you can set image ROI ( Region of Interest) , crop the ROI and save it as another image. /* After detecting the rectangle points, Do as follows */ /* sets the Region of Interest Note that

I am new to Restful concept and have to design a simple API for a media analysis service I need to set up, to perform various tasks, e.g. face analysis, region detection, etc. on uploaded images and video. Outline of my initial design is as follows: Client POSTs a configuration XML file to http://manalysis.com/facerecognition . This creates a profile that can be used for multiple analysis sessions. Response XML includes a ProfileID to refer to this profile. Clients can skip this step to use the default config parameters Client POSTs video data to be analyzed to http://manalysis.com

I have installed opencv 3.1.0 with extra modules, but when I try to use >>> s = cv2.face.MinDistancePredictCollector() it returns an error Traceback (most recent call last): File "<pyshell#5>", line 1, in <module> s.MinDistancePredictCollector() AttributeError: 'module' object has no attribute 'MinDistancePredictCollector' I also checked the documentation: >>> help(cv2.face) Help on module cv2.face in cv2: NAME cv2.face FILE (built-in) FUNCTIONS StandardCollector_create(...) StandardCollector_create([, threshold]) -> retval createEigenFaceRecognizer(...) createEigenFaceRecognizer([, num

I'm using eigenfaces (PCA) for face recognition in my code. I used the tutorials in OpenCV's website as a reference. While this works great for recognizing faces (ie it can tell you who is who correctly), the confidence-score based face verification (or imposter detection- verifying whether the face is enrolled in the training set) doesn't work well at all. I compute a Euclidean distance and use it as a confidence threshold. Are there any other ways I could calculate a confidence threshold? I tried using Mahalanobis distance as mentioned in http://www.cognotics.com/opencv/servo_2007_series

In blog Better Biometrics in Android P they said: "To keep users safe, most apps and devices have an authentication mechanism, or a way to prove that you're you. These mechanisms fall into three categories: knowledge factors, possession factors, and biometric factors. Knowledge factors ask for something you know (like a PIN or a password), possession factors ask for something you have (like a token generator or security key), and biometric factors ask for something you are (like your fingerprint, iris, or face)". But when I read in BiometricPrompt API, I can't see document for iris or face,