OpenCV for Unity
2.6.3
Enox Software / Please refer to OpenCV official document ( http://docs.opencv.org/4.10.0/index.html ) for the details of the argument of the method.
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Minimum Average Correlation Energy Filter useful for authentication with (cancellable) biometrical features. (does not need many positives to train (10-50), and no negatives at all, also robust to noise/salting) More...
Public Member Functions | |
void | salt (string passphrase) |
optionally encrypt images with random convolution More... | |
void | train (List< Mat > images) |
train it on positive features compute the mace filter: h = D(-1) * X * (X(+) * D(-1) * X)(-1) * C also calculate a minimal threshold for this class, the smallest self-similarity from the train images More... | |
bool | same (Mat query) |
correlate query img and threshold to min class value More... | |
Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm | |
IntPtr | getNativeObjAddr () |
virtual void | clear () |
Clears the algorithm state. More... | |
virtual bool | empty () |
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More... | |
void | save (string filename) |
virtual string | getDefaultName () |
Public Member Functions inherited from OpenCVForUnity.DisposableObject | |
void | Dispose () |
void | ThrowIfDisposed () |
Static Public Member Functions | |
static new MACE | __fromPtr__ (IntPtr addr) |
static MACE | load (string filename, string objname) |
constructor More... | |
static MACE | load (string filename) |
constructor More... | |
static MACE | create (int IMGSIZE) |
constructor More... | |
static MACE | create () |
constructor More... | |
Static Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm | |
static Algorithm | __fromPtr__ (IntPtr addr) |
Static Public Member Functions inherited from OpenCVForUnity.DisposableObject | |
static IntPtr | ThrowIfNullIntPtr (IntPtr ptr) |
Protected Member Functions | |
override void | Dispose (bool disposing) |
Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject | |
DisposableOpenCVObject () | |
DisposableOpenCVObject (IntPtr ptr) | |
DisposableOpenCVObject (bool isEnabledDispose) | |
DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose) | |
Protected Member Functions inherited from OpenCVForUnity.DisposableObject | |
DisposableObject () | |
DisposableObject (bool isEnabledDispose) | |
Additional Inherited Members | |
Properties inherited from OpenCVForUnity.DisposableObject | |
bool | IsDisposed [get, protected set] |
bool | IsEnabledDispose [get, set] |
Minimum Average Correlation Energy Filter useful for authentication with (cancellable) biometrical features. (does not need many positives to train (10-50), and no negatives at all, also robust to noise/salting)
see also: [Savvides04]
this implementation is largely based on: https://code.google.com/archive/p/pam-face-authentication (GSOC 2009)
use it like:
you can also use two-factor authentication, with an additional passphrase:
save/load your model:
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constructor
IMGSIZE | images will get resized to this (should be an even number) |
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constructor
IMGSIZE | images will get resized to this (should be an even number) |
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protectedvirtual |
Reimplemented from OpenCVForUnity.CoreModule.Algorithm.
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static |
constructor
filename | build a new MACE instance from a pre-serialized FileStorage |
objname | (optional) top-level node in the FileStorage |
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static |
constructor
filename | build a new MACE instance from a pre-serialized FileStorage |
objname | (optional) top-level node in the FileStorage |
void OpenCVForUnity.FaceModule.MACE.salt | ( | string | passphrase | ) |
optionally encrypt images with random convolution
passphrase | a crc64 random seed will get generated from this |
bool OpenCVForUnity.FaceModule.MACE.same | ( | Mat | query | ) |
correlate query img and threshold to min class value
query | a Mat with query image |
void OpenCVForUnity.FaceModule.MACE.train | ( | List< Mat > | images | ) |
train it on positive features compute the mace filter: h = D(-1) * X * (X(+) * D(-1) * X)(-1) * C
also calculate a minimal threshold for this class, the smallest self-similarity from the train images
images | a vector<Mat> with the train images |