Face Recognition

Face Recognition

App ID	ch.zhaw.facerecognition
Size	54.4 MB
Version	1.5.1
Updated	2017-05-28
Developer	Qualeams

Apps in the Same Category:

• ASUS AiCam 2.0.73.0
• People & Playground! Battle Game 2.0
• Haptic 1.3
• MX Player Codec (ARMv7) 1.10.50
• Gravity Native 0.2.2
• YASNAC – SafetyNet Checker v1.1.5.r65.15110ef310
• MX Player Codec (ARMv6 VFP) 1.7.39
• Guide 1.0
• Youtubers 3.4
• Wafa Santé 2.10.0

• <<
• 1
...
• 3
• 4
• 5
• 6
• 7
• 8
• 9
• 10
• 11
• 12
• 13
...
• 28
• >>

Face Recognition can be used as a test framework for several face recognition methods including the Neural Networks with TensorFlow and Caffe.

It includes following preprocessing algorithms:
– Grayscale
– Crop
– Eye Alignment
– Gamma Correction
– Difference of Gaussians
– Canny-Filter
– Local Binary Pattern
– Histogramm Equalization (can only be used if grayscale is used too)
– Resize

You can choose from the following feature extraction and classification methods:
– Eigenfaces with Nearest Neighbour
– Image Reshaping with Support Vector Machine
– TensorFlow with SVM or KNN
– Caffe with SVM or KNN

The manual can be found here https://github.com/Qualeams/Android-Face-Recognition-with-Deep-Learning/blob/master/USER%20MANUAL.md

At the moment only armeabi-v7a devices and upwards are supported.

For best experience in recognition mode rotate the device to left.
_______________________________________________________________

TensorFlow:

If you want to use the Tensorflow Inception5h model, download it from here:
https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip

Then copy the file “tensorflow_inception_graph.pb” to “/sdcard/Pictures/facerecognition/data/TensorFlow”

Use these default settings for a start:
Number of classes: 1001 (not relevant as we don’t use the last layer)
Input Size: 224
Image mean: 128
Output size: 1024
Input layer: input
Output layer: avgpool0
Model file: tensorflow_inception_graph.pb
———————————————————————————————————
If you want to use the VGG Face Descriptor model, download it from here:
https://www.dropbox.com/s/51wi2la5e034wfv/vgg_faces.pb?dl=0

Caution: This model runs only on devices with at least 3 GB or RAM.

Then copy the file “vgg_faces.pb” to “/sdcard/Pictures/facerecognition/data/TensorFlow”

Use these default settings for a start:
Number of classes: 1000 (not relevant as we don’t use the last layer)
Input Size: 224
Image mean: 128
Output size: 4096
Input layer: Placeholder
Output layer: fc7/fc7
Model file: vgg_faces.pb
_______________________________________________________________

Caffe:

If you want to use the VGG Face Descriptor model, download it from here:
http://www.robots.ox.ac.uk/~vgg/software/vgg_face/src/vgg_face_caffe.tar.gz

Caution: This model runs only on devices with at least 3 GB or RAM.

Then copy the files “VGG_FACE_deploy.prototxt” and “VGG_FACE.caffemodel” to “/sdcard/Pictures/facerecognition/data/caffe”

Use these default settings for a start:
Mean values: 104, 117, 123
Output layer: fc7
Model file: VGG_FACE_deploy.prototxt
Weights file: VGG_FACE.caffemodel

_______________________________________________________________

The license files can be found here https://github.com/Qualeams/Android-Face-Recognition-with-Deep-Learning/blob/master/LICENSE.txt and here https://github.com/Qualeams/Android-Face-Recognition-with-Deep-Learning/blob/master/NOTICE.txt