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Face recognition method and device
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A face recognition technology to be recognized, applied in the field of face recognition, can solve problems such as poor user experience and reduced recognition efficiency, and achieve the effect of solving a large amount of data, reducing the number of feature comparisons, and reducing the scope of search
Pending Publication Date: 2019-07-09
NATIONZ TECH INC
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[0005] The present invention provides a face recognition method and its device to solve the problem that in the existing face recognition method, when the number of recognition is large, the recognition efficiency will be significantly reduced, resulting in poor user experience
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Embodiment 1
[0043] figure 1 For the flow chart of the face recognition method provided in Embodiment 1 of the present invention, please refer to figure 1 , the face recognition method provided in this embodiment includes the following steps:
[0044] S101: Extract at least one face feature value from the face image to be recognized;
[0045] S102: Perform category analysis on the at least one facial feature value, and determine corresponding category information;
[0046] S103: Determine a face feature information set corresponding to the category information from a preset face database according to the category information;
[0047] S104: Perform one-to-one comparative analysis of the at least one face feature value and the set of face feature values, and obtain a face recognition result.
[0048] In some embodiments, the at least one facial feature value can be of the same category or of different categories. When the same category is acquired, only one category of people needs to be...
Embodiment 2
[0077] image 3 For the schematic structural diagram of the face recognition device provided in Embodiment 2 of the present invention, please refer to image 3 , the face recognition device 10 provided in this embodiment specifically includes: an extraction module 11, a category determination module 12, a query module 13 and a processing module 14, wherein
[0078] The extraction module 11 is used to extract at least one facial feature value from the facial image to be recognized;
[0079] The category determination module 12 is used to perform category analysis on the at least one facial feature value, and determine corresponding category information;
[0080] The query module 13 is used to determine the set of facial feature information corresponding to the category information from the preset face database according to the category information;
[0081] The processing module 14 is configured to compare and analyze the at least one face feature value and the set of face fe...
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Abstract
The invention provides a face recognition method and device. The method comprises the following steps: determining corresponding category information according to an extracted face characteristic value; calling a corresponding human face characteristic value set from a preset human face database according to the category information and comparing the human face characteristic value set so as to obtain a face recognition result. Based on the recognition method, a terminal obtains a face characteristic value of a face image to be identified; only simple category contrast is needed; face characteristic values are obtained in a small set and detailed comparison is carried out; therefore, the feature comparison quantity of the terminal during identification is greatly reduced; compared with theprior art, the method has the advantages that the characteristic value searching range is reduced, compared with the prior art, the speed of large-scale face recognition is greatly increased from one-to-one comparison with all known characteristic values to one-to-one comparison with the characteristic values in the same class, the problem that the data size of the terminal is large is solved, and the use experience of a user is enhanced.
Description
technical field [0001] The invention relates to the technical field of face recognition, in particular to a face recognition method and a device thereof. Background technique [0002] With the continuous development of terminal technology, especially for the field of terminal face recognition, most of the methods currently used are: using neural network algorithms to extract eigenvalues from faces, and the eigenvalues are often an array, so that similar faces The eigenvalues between faces are relatively close, and the eigenvalues corresponding to faces with large differences are also far away. The distance between eigenvalues can be defined as cosine distance, various norms, and so on. If the distance between the feature values corresponding to two faces is less than a given threshold, then the two faces are considered to belong to the same person. [0003] Under this approach, a face recognition system would include a database of known faces, with feature valu...
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