Method for identifying human face subspace based on geometry preservation
A space recognition and subspace learning technology, applied in the field of face subspace recognition based on geometry preservation, can solve the problem of not being able to find the essential structure well, and achieve the effect of strong discriminating ability.
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[0022] The embodiments of the present invention are described in detail below: this embodiment is implemented under the premise of the technical solution of the present invention, and detailed implementation methods and processes are provided, but the protection scope of the present invention is not limited to the following embodiments.
[0023] The embodiment adopts a public face database: YALE database. The YALE database contains 15 people with 11 images for each person. Each image varies in pose, expression, lighting, etc. First stack the rows (columns) of the face image into a one-dimensional vector set: X=[x 1 ,...,x N ]. For each person, randomly select p (=3, 5) samples for training, and the rest for recognition. For each given p, 20 sets of random training-recognition sample sets are generated, and the average recognition rate is calculated on this basis. Next, the dimensionality of the face image is reduced to N-1 by principal component analysis.
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