| 摘要 |
The invention concerns a method to compare two data obtained from a sensor or interface, carried out by processing means of a processing unit, the method comprising the computing of a similarity function between two feature vectors of the data to be compared,;characterized in that each feature vector of a datum is modelled as the summation of Gaussian variables, said variables comprising:
a mean of a class to which the vector belongs,an intrinsic deviation, andan observation noise of the vector,;each feature vector being associated with a quality vector comprising information on the observation noise of the feature vector,;and in that the similarity function is computed from the feature vectors and associated quality vectors. |
| 主权项 |
1. A method to compare two data obtained from a sensor or interface, implemented by a processor, the method comprising computing a similarity function between two feature vectors x,y of the data to be compared,Wherein each feature vector of a datum is modelled as the summation of three independent Gaussian variables μ+ω+ε, where said variables are:
a mean μ of a class to which the vector belongs, an intrinsic deviation ω, and an observation noise ε of the vector,each feature vector x being associated with a quality vector qx comprising information on the observation noise of the feature vector, the components of the quality vector being generated as a function of type of datum and type of features forming the feature vector,and wherein the similarity function is computed from the feature vectors x,y and the associated quality vectors as a function of the covariance matrixes of the components of the feature vectors, and the observation noise covariance matrix of each feature vector is obtained as a function of the associated quality vector. |
