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It is an overview of HMMDemo application. See also hypertext manual on it.
This face recognition tool gives the computer the ability to recognize a face from image files (BMP format) or directly from an USB camera. The system requirements for this application are a Pentium® processor-based computer and Microsoft* Windows* NT 4.0, 98, or 2000. The face recognition uses the
embedded hidden Markov model and implements the method described in "Face recognition using an embedded HMM" .[1]
Opens a new document.
[2]
Opens an existing database or an image file in BMP format.
[3]
Creates a new database. It gives the user the ability to specifty the
file location where the information is to be stored.
[4]
Adds a face to the training set. The rectangle in the right panel
should bound the user's face. If the rectangle is misplaced or does
not exist, create one by left-click and dragging a rectangle. If the
left panel is not focused on a particular user, a dialog box will
appear. In this box enter the name of the captured face. If the left
panel is focused (by double-clicking a face) on a person, the captured
face will automatically be added to the current set.
[5]
Deletes an image from the training set or an entire set of images.
[6]
Zooms in the images in the database (left panel).
[7]
Zooms out the images in the database (left panel).
[8]
Toggles video capture.
[9]
Specifies the parameters of the video, the resolution of the image, the depth and size of
the video frames.
[10]
Launches the capture device properties for your USB camera.
[11]
Train the face model. If the left panel is not focused on a set, all
sets will be trained. If the left panel is focused on a set, the
current set is trained.
[12]
Run recognition algorithm on image area within bounding box in the
right panel. If there is no bounding box, create one by left-click and
dragging a rectangle.
[13]
Display about box.
[14]
Not enabled
After capturing several instances for a person, train the face model for that person by clicking button [10]. The models can be trained one by one or all at a once. To train one person, double-click the person to be trained and click button [10]. To train everyone, make sure the left panel is not focused by double-clicking any whitespace in the left panel and click button [10]. Note that when an image is added or deleted from a particular set, that set needs to be retrained.