Face database quick retrieval technology
A retrieval technology and database technology, which is applied in the field of fast retrieval of face databases, can solve the problems of taking too long and the real-time performance of the application is reduced, and achieves the effect of increasing the comparison speed, reducing the candidate records, and improving the practicability and real-time performance.
Active Publication Date: 2020-03-10
SHANDONG INSPUR SCI RES INST CO LTD
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[0003] Under this method, many face recognition scenarios require real-time recognition performance, but when there are too many people in the face database, the process of finding the minimum distance will take too long, resulting in a decline in the real-time performance of the application, or even impossible. accept
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[0029] In order to enable those skilled in the art to better understand the solutions of the present invention, the present invention will be further described in detail below in conjunction with specific embodiments. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.
[0030] A preferred embodiment is given below:
[0031] like figure 1 , 2 As shown, in this embodiment, a method for establishing an orderly segmentation of the face database is first proposed, which ensures that each sub-interval of the division is orderly; then, based on the sub-intervals of the division, a method for face recognition is proposed. A method for quickly comparing face feature vectors.
[0032] (1) Establish an orderl...
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The invention relates to the field of artificial intelligence, and particularly provides a face database rapid retrieval technology. Compared with the prior art, the method has the advantages that theface feature vector output by the face recognition model is the multi-dimensional vector, each dimension is the floating point numerical scalar, and the space formed by the face feature vectors is considered as the Rn space. The method is characterized by comprising the following steps: step 1, establishing ordered segmentation for a face database, and ensuring that each divided sub-interval is ordered; and step 2, based on the divided sub-intervals, comparing the face feature vectors during face recognition, and judging partitions according to the distance between the feature vectors and thecenter vector. According to the method for carrying out partition storage on the face records in the database in advance according to the distance, indexes are properly established, candidate recordsneeding to be searched for can be greatly reduced when the faces are recognized, and the comparison speed is increased.
Description
technical field [0001] The invention relates to the field of artificial intelligence, and specifically provides a fast retrieval technology of a human face database. Background technique [0002] With the development of artificial intelligence and deep learning technology, the deep neural network model has been widely used in face recognition tasks, and has greatly improved the accuracy of face recognition. The trained face recognition model calculates the face feature vectors of all personnel and stores them in the database. When identifying an employee, calculate the feature vector of the face to be recognized in the model calculation, and then calculate the vector The distance to all feature vectors in the database, if the minimum value of the distance is less than the preset threshold δ, it is judged as the same person; otherwise, it is judged that the person is not in the database. [0003] Under this method, many face recognition scenarios require real-time recognitio...
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IPC IPC(8): G06F16/51G06F16/53G06K9/00
CPCG06F16/51G06F16/53G06V40/16
Inventor 高岩金长新郝虹姜凯
Owner SHANDONG INSPUR SCI RES INST CO LTD