EP4014144A1 - Procédé d'identification d'une personne au moyen d'une reconnaissance faciale, appareil d'identification et produit-programme informatique - Google Patents

Procédé d'identification d'une personne au moyen d'une reconnaissance faciale, appareil d'identification et produit-programme informatique

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Publication number
EP4014144A1
EP4014144A1 EP20761139.3A EP20761139A EP4014144A1 EP 4014144 A1 EP4014144 A1 EP 4014144A1 EP 20761139 A EP20761139 A EP 20761139A EP 4014144 A1 EP4014144 A1 EP 4014144A1
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EP
European Patent Office
Prior art keywords
data
person
identified
transformation
data record
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
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EP20761139.3A
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German (de)
English (en)
Inventor
Andreas Wolf
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Bundesdruckerei GmbH
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Bundesdruckerei GmbH
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Publication date
Application filed by Bundesdruckerei GmbH filed Critical Bundesdruckerei GmbH
Publication of EP4014144A1 publication Critical patent/EP4014144A1/fr
Pending legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/168—Feature extraction; Face representation
    • G06V40/171—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/161—Detection; Localisation; Normalisation
    • G06V40/165—Detection; Localisation; Normalisation using facial parts and geometric relationships
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/172—Classification, e.g. identification

Definitions

  • the invention relates to a method for identifying a person by means of facial recognition, an identification device and a computer program product.
  • Processes for identifying people by means of face recognition are widely used today.
  • facial image data of the person to be identified are processed.
  • One or more face recognition algorithms are used here to evaluate the face image data for personal identification.
  • Various face recognition algorithms are known as such.
  • two-dimensional biometric face recognition which uses commercially available cameras for recording
  • three-dimensional (3D) recording of the face for example by means of stripe projection.
  • the face recognition algorithms are implemented for machine face recognition with the help of software applications that can be executed on one or more data processing devices to carry out the personal identification by means of face recognition.
  • personal identification based on face recognition can also be carried out manually or not by machine.
  • a person who is supposed to carry out the test for example security personnel, can be shown a comparison facial image on a display device so that the person performing the identification can compare this with a live image, a photo or the face of the person standing in front of them.
  • Document DE 102015 108351 A1 discloses an identification server for identifying a person to be identified, which has the following: a memory for providing a plurality of personal data records that are assigned to different people, each personal data record being transformed by means of a personalized transformation rule comprises a biometric reference feature of a person, a communication interface for receiving a person identification via a communication network, the person identification being assigned to the person to be identified, and a processor which is designed to use the person identification received to provide an indication of the personalized transformation mation rule, which is assigned to the person to be identified, read from the memory, wherein the communication interface is designed to send a request to transmit a biometric feature of the person to be identified transformed by means of the personalized transformation rule over the communication network.
  • the request includes the reference to the personalized transformation rule.
  • the communication interface is also designed to receive the transformed biometric feature of the person to be identified via the communication network.
  • the processor is designed to compare the received transformed biometric feature with the transformed biometric reference feature in order to identify the person to be identified.
  • the object of the invention is to specify a method for identifying a person by means of face recognition, an identification device and a computer program product with which the usability of face recognition is facilitated in compliance with data protection provisions in various fields of application.
  • a method for identifying a person by means of facial recognition is created, in which case a depersonalized data record is provided in an identification device.
  • the depersonalized data record is calculated from a personalized data record by means of a data transformation in accordance with a transformation rule.
  • the personalized data record includes facial image data for a person to be identified, on the basis of which the person to be identified can be identified with the aid of at least one face recognition algorithm.
  • the depersonalized data record is, based on the personalized data record, due to the application of the data transformation on according to the transformation rule so that the person to be identified can no longer be identified with the aid of the at least one face recognition algorithm based on the depersonalized data record, which includes facial image data that has been changed in accordance with the transformation rule.
  • the method further comprises the following steps: providing transformation data, which indicate the transformation rule, in the identification device; Calculating a re-personalized data record from the depersonalized data record, the re-personalized data record, starting from the depersonalized data record, being changed by means of a further data transformation according to an at least partial reversal of the transformation rule so that the person to be identified is changed using the re-personalized data record can be identified with the aid of the at least one face recognition algorithm and / or at least one other face recognition algorithm which is different from the at least one face recognition algorithm; Providing a comparison data set which comprises current face image data for the person to be identified; and identifying the person using the re-personalized data record, the comparison data record and the at least one face recognition algorithm and / or the at least one other face recognition algorithm.
  • an identification device which has one or more processors which are set up to identify a person by means of face recognition: providing a depersonalized data record, the depersonalized data record being calculated from a personalized data record by means of a data transformation according to a transformation rule , the personalized data record includes facial image data for a person to be identified, on the basis of which the person to be identified can be identified with the aid of at least one face recognition algorithm, and the depersonalized data record, based on the personalized data record, based on the application of the data transformation according to the
  • the transformation rule is changed in such a way that the person to be identified, using the depersonalized data record, has changed his face in accordance with the transformation rule tstruckarian includes, with the help of the at least one face recognition algorithm can no longer be identified.
  • the processor or processors are set up to carry out the following: Providing transformation data that indicate the transformation rule; Calculating a re-personalized data record from the depersonalized data record, the re-personalized data record, starting from the depersonalized data record, being changed by means of a further data transformation according to an at least partial reversal of the transformation rule so that the one to be identified Person can be identified on the basis of the re-personalized data record with the aid of the at least one face recognition algorithm and / or at least one other face recognition algorithm which is different from the at least one face recognition algorithm; Providing a comparison data set which comprises current facial image data for the person to be identified; and identifying the person using the re-personalized data record, the comparison data record and the at least one face recognition algorithm and / or the at least one other face recognition algorithm.
  • a computer program product is also created.
  • the personalized data set was made in accordance with the transformation rule when deriving or determining the depersonalized data set changed in such a way that such a machine face recognition is no longer possible at least with the at least one face recognition algorithm.
  • it can be determined experimentally from when the originally personalized data record is depersonalized due to a change in accordance with the transformation rule, which is optionally carried out in successive change steps, so that the machine face recognition based on the data record thus depersonalized is not more is possible.
  • a “distance” between the personalized data set and the depersonalized data set ie the difference between the facial image data and the changed facial image data, can depend on the specific face recognition algorithm.
  • face recognition algorithms With different face recognition algorithms, different data transformations can be used for depersonalization in order to determine the depersonalized data set in each case. Face recognition algorithms are known as such in various embodiments and can be used for the experimental determination of the depersonalized data set.
  • the transformation rule for depersonalization can be determined once and then used for different applications without the need for a new (experimental) determination. So it does not have to be determined (again) with each depersonalization whether a current personalized data record is “sufficiently” depersonalized. Rather, a previously determined transformation rule can be used without such a check.
  • the transformation rule specifies how the data transformation for calculating or determining the depersonalized data record from the personalized data record was carried out as a whole. For example, it can be a data transformation protocol.
  • the transformation rule can be configured so that a complete reversal or inversion of the data transformation is enabled on the basis of the information it comprises, so that on the basis of the knowledge of the transformation rule, the depersonalized data record is converted into the personalized data record, which is the starting point for the data transformation formed, converted again or calculated back.
  • a transformed (depersonalized) data record is provided, which can be stored in a storage device, for example a local memory and / or a central database, possibly even without the consent of the based data record identifiable person.
  • a storage device for example a local memory and / or a central database
  • the depersonalized data record, based on the personalized data record has been "falsified” or changed to such an extent that it can no longer be assigned to the person at least with the help of the at least one face recognition algorithm, so that the person can be assigned using the depersonalized data record with which at least one face recognition algorithm cannot be identified by machine.
  • This facilitates the provision and storage of electronic data for facial recognition applications, for example in connection with access control.
  • the transformation data must also be provided, which indicate the transformation rule or provide information about the data transformation that can be evaluated electronically.
  • Machine face recognition with the aid of the at least one face recognition algorithm can only be carried out on the basis of the depersonalized data record if these transformation data are provided.
  • the person to be identified can be given control of the transformation data so that it cannot be used without authorization.
  • the person to be identified can be identified on the basis of the personalized data record using at least one additional face recognition algorithm.
  • the depersonalized data record is then, starting from the personalized data record, changed by means of data transformation in accordance with the transformation rule so that the person to be identified is based on the depersonalized based data record is also and additionally no longer identifiable with the help of the at least one additional face recognition algorithm.
  • the depersonalized data record is generated, it is checked experimentally whether the personalized data record, optionally changed piece by piece, can still be evaluated by machine with the at least one and the at least one additional face recognition algorithm for personal identification. If this is no longer possible in both cases, the original personalized data record is “sufficiently” depersonalized or changed.
  • the data transformation according to the transformation rule for depersonalizing can lead to the depersonalized data record not only being sufficient (evaluable) for machine face recognition not only for the at least one face recognition algorithm, but also for a large number of face recognition algorithms, even if this is done when creating the depersonalized one Dataset was optionally determined experimentally only for one or more of the multitude of face recognition algorithms.
  • the at least one additional face recognition algorithm can be used additionally or alternatively when identifying the person, after the re-personalized data set has been determined beforehand.
  • landmarks for the face of the person to be identified can be changed according to the face image data by means of data transformation of the transformation rule.
  • Landmarks for use in machine face recognition are known as such in a defined form, so that one or more landmarks can be selected in order to use them in the data transformation to “falsify” the face displayed by the face image data.
  • Landmarks as such are defined, for example, in ISO / IEC 14496-2: 2004 (Information technology - Coding of audio-visual objects - Part 2: Visual).
  • ISO / IEC 39794-5: 2020 Information technology - Extensible biometric data interchange formats - Part 5: Face image data
  • ISO / IEC 19794-5 2011 (Information technology - Biometrics - Biometric data interchange formats - Part 5: Face image data) did this before.
  • a change to one or more landmarks can be carried out step by step, for example, in order to determine when the originally personalized data set is depersonalized in such a way that machine face recognition with the at least one face recognition algorithm is no longer possible. Provision can be made for one or more change limits within which the change takes place during the data transformation to be specified for the one or more landmarks.
  • the landmark limits can specify minimum changes and / or maximum permitted changes.
  • At least some of the landmarks can be changed in each case by different transformation steps which are determined, for example, randomly, that is to say according to the random principle, for example with regard to direction and distance, are shifted by the respective landmark.
  • the changes to the landmarks can be at least partially different or also independent of one another, i.e., for example, that the landmarks are not all shifted in the same direction and by the same distance (although the changes may still be dependent on the error limits). In particular, this changes the arrangement of at least some of the landmarks relative to one another.
  • the landmarks can then be reset to their original values (within permissible error tolerances) in order to determine the re-personalized data record.
  • the facial image data can be (re) determined in whole or in part from the personalized data record.
  • the transformation rule provides information about the changes made to the landmark or landmarks during depersonalization.
  • the face is triangulated on the basis of the original and the new landmarks. For all triangles determined here can then compared the edge lengths. It can be provided that, during depersonalization, each individual edge length does not differ by more than a threshold value, for example. Provision can be made for the changed facial image data to be determined in such a way that the sum of all differences does not differ by more than an additional threshold value, which is also to be determined.
  • the transformation data that indicate the transformation rule can be read in via a communication interface of the identification device.
  • the transformation data can be read in via the communication interface, for example from a mobile or portable data memory, for example a so-called smart card or a personalized token on which the transformation data was previously stored.
  • the transformation data can be made available to the person to be identified so that the person to be identified brings the transformation data with him, for example to a face recognition location, for example an access control with the aid of the identification device.
  • the identification device itself does not have the transformation data before it is read in or received via the communication interface.
  • provision can be made for the transformation data to be received by a remote server upon request from the identification device.
  • An electronic signature can be provided for the transformation data.
  • the identification device can have an image data acquisition device for acquiring the current face image data, by means of which the current face image data of the person to be identified can be acquired during identification, the face image data being 2D data, for example as a still or moving image from a camera, and / or 3D data, for example generated using pattern projection onto the face, may contain.
  • the identification device can transmit an access authorization signal to an access control device in order to authorize the person for access and / or, after unsuccessful identification, a corresponding access refusal signal to deny the person access.
  • “Access” can mean “physical” access or access to a room, building, site and the like, which is granted or denied, for example, by appropriately activating a door opener or the like, access or access to an object, eg authorization to open a container, safe, etc., or even a "virtual" access to a computer system, electronic device and the like, as understood by logging in, unlocking, etc.
  • the personalized data record can be iteratively changed when the data transformation is carried out according to the transformation rule, after which successive iterative steps are checked whether the person to be identified can still be identified using the current changed / (partially) depersonalized data record with the help of the at least one face recognition algorithm is.
  • There is a step-by-step change in the personalized data record for depersonalization i.e. a step-by-step increase in the distance between the personalized data record (facial image data) and the changed data record for the depersonalized (changed facial image data), which represents a step-by-step or piece-wise change in the data from the facial image - means the face of the person to be identified.
  • the change is continued if, when checking the current depersonalized data record, it is found that the person to be identified can still be identified with the aid of the at least one face recognition algorithm based on this current data record. Otherwise the iterative (step-by-step) data transformation is aborted.
  • the transformation rule can then display or document the partial data transformations carried out in the individual change steps and / or (only) the (maximum) change in the personalized data record.
  • the depersonalized data record can be configured (by means of the change made to depersonalize) that the person to be identified can be identified with the human eye on the basis of the changed facial image data.
  • the data transformation (change) of the personalized data set carried out for depersonalization is limited to the effect that non-machine or manual face recognition by a person is still possible if the person has a face image based on the depersonalized data set (changed face image data) and a comparison image compares the person to be identified. It is known that people are still able to carry out a person identification by means of image comparison if the face recognition algorithms that are used for machine face recognition already fail (for example as explained above with regard to the changes to the landmarks) .
  • This embodiment enables, for example, access control in which the access control staff is shown the facial image on the basis of the depersonalized data record, so that the access control staff can display this image or display of the face with a comparison image of the person to be identified can compare, for example, a live image or the person at the access control. If machine face recognition is dispensed with here, the transformation data does not need to be provided. On the one hand, the original personalized data record is depersonalized (depersonalized data record), so that the requirements for the electronic storage of this data record are lower than in comparison with the storage of the personalized data record. On the other hand, manual face recognition is still possible.
  • the determination of the limit at which the depersonalized data record still enables manual face recognition can be carried out experimentally by outputting the changed data record (for example piece by piece) via a display device and recording a user input (test personnel) which shows whether the output has been issued Facial image in comparison to a comparison image can still be assigned to the comparison image by the testing personnel, so that personal identification is made possible or not.
  • change limits for the landmarks used for face recognition can be specified in the transformation rule so that the depersonalization is carried out within limits that lead to a depersonalized data record that still enables manual face recognition.
  • the changed face image data and the current face image data can be output via an image output device in order to be made available for manual personal identification.
  • the display of the changed face image data and the current face image data on the image output device enables a person to compare the faces in order to carry out a manual personal identification, for example as part of an access control.
  • a method for identifying a person by means of face recognition is created, in which case a depersonalized data set is provided in an identification device.
  • the depersonalized data record is calculated from a personalized data record by means of a data transformation according to a transformation rule.
  • the personalized data record includes facial image data for a person to be identified, on the basis of which the person to be identified can be identified with the aid of at least one face recognition algorithm.
  • the depersonalized data record is changed due to the application of the data transformation in accordance with the transformation rule so that the person to be identified is based on the depersonalized data record, which includes facial image data changed in accordance with the transformation rule, with the help of the at least one system.
  • vision recognition algorithm is no longer identifiable.
  • the method further comprises outputting the depersonalized data set, in particular the changed facial image data, via an output device, in such a way that the changed facial image is displayed so that it is available for manual face recognition.
  • the changed face image data (still) enable manual face recognition, but not machine. Provision can be made for a user input to be received via an input device of the identification device, for example a keyboard or a touch-sensitive surface, which indicates whether the person could be identified or not. This signal can then be processed further, for example for the automated operation of an access control device.
  • FIG. 1 shows a schematic representation of an arrangement with an identification device
  • FIG. 2 shows a schematic illustration for explaining a method for identifying a person by means of face recognition.
  • the identification device 1 shows a schematic representation of an arrangement with an identification device 1, with which machine personal identification can be carried out.
  • the identification device 1 has a processor 2 which is connected in terms of data technology to a memory device 3 and a communication interface 4, so that electronic data can be exchanged.
  • a plurality of processors may alternatively be provided.
  • the communication interface 4 can be set up, for example, to read out a mobile or portable data memory 5, for example a smart card, in a contactless or contact-based manner.
  • An output device 6 can be coupled to the identification device 1, for example an image data output device, which is shown in FIG. 1 by means of dashed lines.
  • the output device 6 can identify the device 1 or separately therefrom be educated. Part of the data exchange, the identification device 1 can be temporarily or permanently connected to a server device 7.
  • the identification device 1 can be used in conjunction with an access control system (not shown) which is set up for access control using machine and / or manual face recognition.
  • a depersonalized data set is provided in the identification device 1, for example in such a way that the depersonalized data set is stored in the storage device 2.
  • the depersonalized data record has previously been calculated from a personalized data record by means of a data transformation in accordance with a transformation rule. This can take place in the identification device 1 itself or in another data processing device (not shown).
  • the personalized data record from which the depersonalized data record is derived includes facial image data for a person to be identified. Using the face image data, the person to be identified can be identified with the aid of at least one face recognition algorithm in the context of machine face recognition.
  • the personalized data record with the face image data can be processed in such a way that a person identification can be carried out from a comparison with a (current) image of the person which is provided for comparison.
  • the at least one face recognition algorithm is therefore able to process the personalized data set and data on the current face image in order to identify the person. Face recognition algorithms are known as such in various embodiments.
  • a data transformation according to the transformation rule is used for the depersonalized data record, so that the personalized data are changed so that the person to be identified (at least) with the depersonalized data record Can no longer be identified using the at least one face recognition algorithm.
  • the face image data are changed into changed face image data in such a way that the at least one face recognition algorithm is no longer able to identify the person in the context of machine face recognition.
  • transformation data are provided in the identification device 1 which indicate the transformation rule. This can be, for example, a log relating to the changes to the data (in particular the facial image data) from the personalized data record when the depersonalized data record is created.
  • the transformation data can include a difference image for the face image data and the changed face image data.
  • the transformation of the depersonalized image into the re-personalized image can be carried out, for example, by completely or partially inverting the processing steps carried out for the change step by step. This may take longer, but it has the advantage that the coding of the change steps (depersonalization) can be done in a very compact manner, since what is to be done with each individual pixel is not determined. For example, the following should be provided: Selecting the landmark 9.3 (that is the tip of the nose); Mark a circle with a 30 pixel radius around this landmark and shift the landmark 9.3 by five pixels to the right and adjust all pixels in the circle proportionally.
  • GIMP GNU Image Manipulation Program
  • the program is free software and can be used free of charge.
  • a pixel-by-pixel differential image can additionally or alternatively be determined as a transformation rule.
  • a re-personalized data record is calculated or determined in the identification device 1 from the depersonalized data record, the re-personalized data record, starting from the depersonalized data record, by means of a further data transformation according to an at least partial reversal or inversion of the transformation rule is changed so that the person to be identified is now based on the re-personalized data set with the help of the at least one face recognition algorithm and / or at least one other or additional face recognition algorithm which is different from the at least one face recognition algorithm is, can be (re) identified by machine.
  • the depersonalized data record can be partially or completely converted back into the personalized data record. With the further data transformation, it is achieved that a machine face recognition is possible again.
  • a comparison data set is provided in step 23, which includes current face image data for the person to be identified
  • the person to be identified is identified in step 24 using the re-personalized data set, the comparison data set and the at least one face recognition algorithm and / or the at least one other face recognition algorithm (machine) identified.
  • the face recognition algorithm processes data from the re-personalized data set and the comparison data set in order to identify the person.
  • the provision of the transformation data (step 21) in the identification device 1 can take place in that the transformation data is read in from the mobile data carrier 5 via the communication interface 4, for example from a so-called smart card 5 or another data token.
  • the depersonalization of the personalized data record (before the depersonalized data record is made available in the identification device 1), provision can be made to limit the depersonalization in such a way that the changed face image data of the depersonalized data record generated during the data transformation still require a non-automatic or manual face recognition by a human being when the changed facial image data of the human being are compared with a comparison image of the person to be identified.
  • the aim of de-personalization is to change a facial image of a person in such a way that it can no longer be assigned to a comparison photo by (selected) machine processes, but can be assigned to a comparison photo by a person with average recognition skills, in order to still allow manual facial recognition enable.
  • Landmarks are determined in the facial image. Depending on their characteristics, this can be some or all of them according to ISO / IEC 14496-2 and / or other landmarks, such as the centers of the eyes according to ISO / IEC 39794-5 or similar features.
  • the certain landmarks are shifted / changed by a random distance in a random direction compared to their original position ("trembled" into a new position).
  • each individual distance should not be greater than a certain threshold value to be defined (maximum change limit). Larger changes in location are rejected as too dissimilar. It can also be provided that the sum of all the distances is not greater than a second threshold value to be determined. Larger cumulative changes in location are also rejected as too dissimilar. On the other hand, it can be provided that the sum of all the distances is at least as large as a third threshold value to be defined, below which the similarity is assumed to be sufficient for machine systems.
  • a certain threshold value to be defined maximum change limit
  • each individual edge length should not differ by more than one additional threshold value. It can be provided that the sum of all differences do not differ by more than one additional threshold value that is also to be determined.
  • the texture of the original face image is then transferred to the new landmark grid using triangulation.
  • Methods known as such from 3D face recognition can be used for this.
  • the triangles can for example be stretched / compressed linearly, but the distortion can also take place in such a way that the edges of the triangles smoothly merge into those of the neighboring triangles and neighboring pixels do not create any sharp transitions in the optical flow. Further projections of the original grid onto the new grid are possible.
  • the threshold values can be determined on the basis of empirical values or experimentally.
  • experimental data are used on a representative set of facial images, such as passport photos and a number of state- of-the-art face recognition method used.
  • the new image can always be tested using an automated method or a selection of automated methods (face recognition algorithms), and the lower threshold value can be omitted.
  • the changed facial image cannot be generated by random positions of the landmarks, but rather using the similarity values generated by the machine comparison method, with the largest of a certain number of possible (smaller and random) changes in position Decrease in the similarity value is used for the next step in an iterative process in a kind of gradient approach.
  • the depersonalized image was generated from the initial image (transformation data). If machine face recognition is required, the (personalized) original can be generated from the changed image by means of inverse processing.

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Abstract

L'invention concerne un procédé et un dispositif (1) d'identification permettant d'identifier une personne au moyen d'une reconnaissance faciale. Le procédé comprend les étapes suivantes : fournir un ensemble de données dépersonnalisées, l'ensemble de données dépersonnalisées étant calculé à partir d'un ensemble de données personnalisées au moyen d'une transformation de données selon une instruction de transformation ; calculer un ensemble de données re-personnalisées à partir de l'ensemble de données dépersonnalisées, l'ensemble de données re-personnalisées, sur la base de l'ensemble de données dépersonnalisées, étant modifié au moyen d'une transformation de données supplémentaire, selon une inversion au moins partielle de l'instruction de transformation, de telle sorte que la personne à identifier est identifiable sur la base de l'ensemble de données re-personnalisées à l'aide du ou des algorithmes de reconnaissance faciale et/ou d'au moins un autre algorithme de reconnaissance faciale, qui est différent du ou des algorithmes de reconnaissance faciale ; fournir un ensemble de données comparatives qui comprend des données d'image faciale actuelles pour la personne à identifier ; et identifier la personne à l'aide de l'ensemble de données re-personnalisées, de l'ensemble de données comparatives et du ou des algorithmes de reconnaissance faciale et/ou du ou des autres algorithmes de reconnaissance faciale. L'invention concerne en outre un produit-programme informatique.
EP20761139.3A 2019-08-16 2020-08-13 Procédé d'identification d'une personne au moyen d'une reconnaissance faciale, appareil d'identification et produit-programme informatique Pending EP4014144A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102019122119.6A DE102019122119A1 (de) 2019-08-16 2019-08-16 Verfahren zum Identifizieren einer Person mittels Gesichtserkennung, Identifizierungsvorrichtung sowie Computerprogrammprodukt
PCT/DE2020/100708 WO2021032248A1 (fr) 2019-08-16 2020-08-13 Procédé d'identification d'une personne au moyen d'une reconnaissance faciale, appareil d'identification et produit-programme informatique

Publications (1)

Publication Number Publication Date
EP4014144A1 true EP4014144A1 (fr) 2022-06-22

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EP20761139.3A Pending EP4014144A1 (fr) 2019-08-16 2020-08-13 Procédé d'identification d'une personne au moyen d'une reconnaissance faciale, appareil d'identification et produit-programme informatique

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US (1) US12444231B2 (fr)
EP (1) EP4014144A1 (fr)
DE (1) DE102019122119A1 (fr)
WO (1) WO2021032248A1 (fr)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP4612704A1 (fr) * 2022-11-02 2025-09-10 Koninklijke Philips N.V. Système intelligent pour rationaliser les communications et réduire les interruptions dans le service de radiologie

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160080943A1 (en) * 2014-08-08 2016-03-17 Kenneth Ives-Halperin Short-range device communications for secured resource access

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102015108351A1 (de) * 2015-05-27 2016-12-01 Bundesdruckerei Gmbh Identifikationsserver zur Identifikation einer zu identifizierenden Person
IL252657A0 (en) * 2017-06-04 2017-08-31 De Identification Ltd System and method for preventing image recognition

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160080943A1 (en) * 2014-08-08 2016-03-17 Kenneth Ives-Halperin Short-range device communications for secured resource access

Also Published As

Publication number Publication date
US12444231B2 (en) 2025-10-14
WO2021032248A1 (fr) 2021-02-25
DE102019122119A1 (de) 2021-02-18
US20220300644A1 (en) 2022-09-22

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