Create an object recognizer using the specific tranning data and parameters

C# | Visual Basic | Visual C++ |
public EigenObjectRecognizer( Image<Gray, byte>[] images, string[] labels, double eigenDistanceThreshold, ref MCvTermCriteria termCrit )
Public Sub New ( _ images As Image(Of Gray, Byte)(), _ labels As String(), _ eigenDistanceThreshold As Double, _ ByRef termCrit As MCvTermCriteria _ )
public: EigenObjectRecognizer( array<Image<Gray^, unsigned char>^>^ images, array<String^>^ labels, double eigenDistanceThreshold, MCvTermCriteria% termCrit )

- images (array< Image<(Of <(Gray, Byte>)>) >[]()[])
- The images used for training, each of them should be the same size. It's recommended the images are histogram normalized
- labels (array< String >[]()[])
- The labels corresponding to the images
- eigenDistanceThreshold (Double)
- The eigen distance threshold, (0, ~1000]. The smaller the number, the more likely an examined image will be treated as unrecognized object. If the threshold is < 0, the recognizer will always treated the examined image as one of the known object.
- termCrit ( MCvTermCriteria %)
- The criteria for recognizer training