EP3695388A1 - Système de contrôle d'une personne - Google Patents
Système de contrôle d'une personneInfo
- Publication number
- EP3695388A1 EP3695388A1 EP18782729.0A EP18782729A EP3695388A1 EP 3695388 A1 EP3695388 A1 EP 3695388A1 EP 18782729 A EP18782729 A EP 18782729A EP 3695388 A1 EP3695388 A1 EP 3695388A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- traveler
- biometric
- feature space
- building
- traveller
- 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
Links
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/20—Individual registration on entry or exit involving the use of a pass
- G07C9/22—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder
- G07C9/25—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition
- G07C9/257—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition electronically
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
- G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
Definitions
- Access control devices for airports are known, for example, from DE 10 2004 048 403 AI. Such access control devices are mainly needed because of the increased security requirements in the airport area to be able to carry out these and the correspondingly more complex controls with the least possible personnel costs while increasing security standards. It is particularly problematic that between the check-in of the passenger and the actual boarding process (boarding) in the plane, possibly people are exchanged.
- a border crossing control device with a person sluice releasing or blocking an access, which is assigned a document read unit and a biometric detection device connected to a control unit of the person sluice.
- the biometric detection device is connected to a database.
- the personal lock is opened or locked.
- an individual, temporary data record is created for each passenger and each flight at the time of booking the flight. This record contains the booking data of the flight and an identification of the flight procedure and the flight data record.
- the flight data record at a boarding unit upstream of the person lock after reconciliation of the identification of the flight operation, further data recorded in the area of this boarding unit leaked, namely at least a scan of a person-identifying document and one or more fingerprints or a facial image.
- Face recognition generally works well. However, this fails in special situations, such as in poor lighting, in different headgear and in groups of people with partial masking of the faces.
- a traveler places his passport or ID card on a scanner in front of a security gate. It reads both the personal data and the biometric passport photo stored on the RFID chip of the document.
- a camera compares the passport photo with the passenger's face. In the background, the system matches the traveler with current wanted lists. If the face matches the biometric passport photo and there is nothing against the passenger, the lock opens.
- Conventional video surveillance systems are based on the evaluation of video images and video sequences. Image content is analyzed in different ways. Different approaches are followed: (i) Only visual information from the captured images is used to compute a signature of the person, (ii) the person is segmented by the image content.
- a person's identification is based on the biometric data derived from the imagery. All of these types of identification require image capturing of a certain quality. In practice, however, this requirement proves to be problematic, as for a corresponding quality, a participation of the person is necessary. In order to compensate for the disadvantages and to improve the recognition rate even without the involvement of the person, it has been proposed to take into account further non-biometric features which are based on frontal resp. Side shots based on color and texture of hair, skin and clothing. However, problems with the recognition and identification of persons are not excluded if the input data does not fulfill a certain quality.
- Travelers today carry a variety of electronic devices with them, such as mobile phones, laptops, headphones, smartwatches, fitness trackers, etc. These can be partially recorded even without the involvement of the traveler and at least partially wirelessly analyzed to obtain a digital impression, the is characteristic of the particular traveler at least during his stay in the building to a certain extent.
- Current electronic devices for end users mobile phones, smartphones, fitness or health trackers, portable computers, readers for electronically stored book content (e-readers), tablet computers, notebooks, etc. have a signature.
- a feature space is identified which, in addition to the non-biometric or biometric features, includes other features characteristic of the traveler (ie, the digital impression) that together uniquely identify the traveler with a certain probability.
- This feature space is gradually supplemented as the traveler travels through the airport, capturing further (biometric or non-biometric) characteristics of the traveler.
- the probability of a correct identification of the traveler then results from the weighted sum of the individual probabilities of the identification features. It is also possible to determine the probability of a correct identification of the traveler from the ratio of the weighted sum of the individual probabilities of the identification features to the maximum possible sum.
- transceivers and sensors which the traveler passes on his way through the building / facility.
- the sensors acquire the values or output data that are characteristic for different (partial) identifications of a traveler.
- These (partial) identifications of the traveler are, on the one hand, his non-biometric or biometric features, such as passport control, ticket completion, camera-controlled passage of a singling lock, a step-length sensor on a passageway, a body height sensor, or the like, and on the other hand, these values are the results of targeted communication of the transceivers with the electronic devices carried by the traveler to obtain his browser signature, the NFC signature of his smartphone, etc.
- These values or output data signal the respective readers, transceivers and sensors to a central controller, which determines the values or output data for determining the individual values for the corresponding features and, in a database, sends the individual values for the respective features to the feature space of a traveler ,
- the more precise identification of a traveler is realized by combining different features, each of which would not sufficiently or only partially identify the traveler.
- biometric eg, facial features, hair color and shape, iris, fingerprint, stride length, height
- non-biometric ⁇ shear characteristics for example, clothing, digital print, ...)
- the digital imprint is the combination of the signature [s] of the personal electronic devices (smartwatch, smartphone, fitness tracker, NFC or Bluetooth devices, etc.) that the traveler accompanies during the passage of a personal lock or the Easypass system leads and other biometric or physical quantities, such as hair color, height, clothing, headgear, facial image, etc.
- the personal electronic devices smart watch, smartphone, fitness tracker, NFC or Bluetooth devices, etc.
- biometric or physical quantities such as hair color, height, clothing, headgear, facial image, etc.
- the probability of a reliable identification then results from the ratio of the weighted sum of the individual probabilities of the identification features to the maximum possible sum.
- This controlled environment may be the ticket counter where the traveler presents his travel document.
- - data collection by means of sensors, transceivers and / or reading devices and providing ⁇ position of the captured data in a database.
- the travel document and the ticket are scanned with the reader, for example.
- a front and / or side image of the traveler's head or face is created with a camera sensor.
- his electronic ⁇ devices are queried by means of appropriate transceiver. Based on this, the traveler's initial feature space is filled, containing the non-biometric, technical, and other characteristics.
- the device characteristics of the devices carried by the traveler are recorded with transceivers specific to the respective device type.
- biometric travel document passport or similar
- ticket ticket
- input device for example in the form of a (plain-language) reading device.
- the traveler when entering the airport, the traveler is identified by an identification unit at the ticket office, already at the building entrance or in advance, and, for example, the flight reservation is linked to his identity.
- This is also a non-biometric feature of the traveler, such as headdress, clothing, presence of digital devices, which are also captured and added to his feature space.
- This feature space is much more meaningful in its complexity than a biometric facial image alone. Therefore, it can be checked much easier and less in the way of the traveler through the airport intervening at different points of the airport. A queue-standing at passage controls is so often avoided.
- the purely optical, camera-based controls in different lighting conditions can be meaningful, if they are supplemented by other based on other factors (stride length, cell phone signature, etc., so) identity comparisons.
- This allows security personnel to perform an unobtrusive reconciliation of electronic documents and certificates without disturbing other passengers, resulting in fewer security-related queues and making overall flow and throughput in the facility or building smoother.
- the data is stored in a variant without probabilities in the database. At a later time these features are detected by a transceiver and already in the transceiver or by the controller the database with probabilities to be compared with the corresponding entries in the feature space.
- FIG. 1 shows, in a schematic plan view, a building or a plant in an exemplary design of an airport in which the solution presented here is implemented.
- FIG. 1 is a schematic plan view of a building in which the solution presented here is realized by way of example.
- a biometric travel document RD in the form of a biometric passport, as information I surname, first name / s, gender, date of birth, a hometown, nationality , Size, photography, issuing authority, date of issue, expiration date, badge number and identification type, data chip with facial image and fingerprints, signature, machine readable zone contains, as well as various electronic devices Gl ... Gn carries with itself, eg Handyteiefon, Laptop, tablet computer, e-reader, wireless headset, smartwatch, fitness tracker, etc.
- the building is subdivided into predetermined areas that the traveler does not enter, or only after checking his identity and / or authorization leave.
- the traveler With access locks ZS, the traveler is enabled or disabled access to the respective predetermined area of the building depending on the traveler's checks. It may be a singling lock where passengers pass through one after another without having to show their travel documents for review. Rather, the system presented here has an electronic control ECU, which is set up with various transceivers SE for communication. Each of these transceivers SE is used to wirelessly contact one or more of the electronic devices Gl ... Gn carried by the traveler when the traveler is in close proximity to these transceivers SE. Thus, the transceivers SE can detect electronic devices Gl ...
- Gn carried by the traveler and at least partially analyze them wirelessly in order to obtain from the devices Gl ...
- Gn device characteristics GK are characteristic of the particular traveler at least during his stay in the building to a certain extent.
- These device characteristics GK can eg Bluetooth devices whose individual and distinctive 48-bit long MAC address or the browser signature in a tablet computer, e-reader or other personal digital assistant, or be stored in the SIM card of the smartphone serial number IMSI.
- the transceivers SE are each capable of and configured to acquire one or more device characteristics GK. For this they each have a local control, which is for example able to handle the communication with a traveler's Bluetooth device, or communicate with a traveler's PDA to read out an IMSI of a telephone SIM card contained therein, etc ,
- an input device T is provided, on the one hand the ticket (ticket) and on the other hand read the traveler's biometric travel document RD, and passed their contents for further processing to the electronic control unit ECU become.
- device characteristics GK of the electronic devices Gl ... Gn of the traveler are detected and, if necessary, recorded with photos or dimensions (for example, stride length, etc.) of the traveler and also forwarded to the electronic control unit ECU.
- This electronic control ECU prepares the received data and sends it to an electronically operated database DB.
- a feature space MR is generated for each traveler in which the device characteristics GK are entered by the transceivers SE as a digital impression of the traveler.
- a certain probability p is calculated in the database DB for the traveler with which it is to be identified.
- This probability p can be e.g. can be calculated from the ratio of a weighted sum of the individual entries of the feature space MR to the maximum possible sum. Other calculations of the weights are possible / conceivable.
- This is done in a variant with, in another variant without the associated (single) or total weighting of the collected data. Subsequently, this data is compared with the previous entries in the feature space of the traveler. If the newer captured data has a better probability p to identify the traveler, these newer captured data may also replace the corresponding historical data in the traveler's feature space.
- the traveler's data is preprocessed to segment and process it for further analysis.
- the individual features of the feature space are evaluated by calculating the quality of the individual features.
- the system (partial) identification of the traveler from its non-biometric and / or biometric characteristics with the digital imprint of Rei ⁇ send aggregated in the feature space MR to a total identification.
- the sensors and transceivers SE are located at one location or different locations within the building near the respective predetermined areas and capture at least non-biometric as well as portions of the traveler's digital imprint when the traveler gets close to one of these predetermined areas.
- These parts of the traveler's digital imprint are signaled to the database DB and weighted accordingly to trigger matching of these parts with the corresponding entries in the traveler's feature space MR.
- the enabling or disabling of the access barriers ZS to the predetermined area of the building is effected for that traveler.
- device characteristics GK of the electronic devices Gl ... Gn and possibly photos of the traveler are detected with the aid of the various transceivers SE located there.
- device characteristics GK this predetermined range is enabled or disabled for the traveler.
- the input device T comprises, in addition to a display unit, for example, a barcode scanner or a document reader, with the addition of a 2-D barcode of a boarding pass or a ticket printed at home and the chip of a personidentifirudden document, ie about a passport, with respect to the biometric image or the RFID data, can be read.
- This document reader can also read and recognize the machine-readable data of the person-identifying document.
- the traveler is asked to legitimize himself; then the input device T triggers the creation of the feature space MR of the traveler in the database DB. Also, a fingerprint reader for one or more fingerprints may be provided to capture the passenger's fingerprints. Finally, the travel document (passport or the like) is read in and fed with the data of the ticket to the feature space MR of the traveler of the database DB.
- the traveler is signaled to make his way through the building, for example, that his check-in process is completed and he should go to the gate.
- the traveler can go through the area and the hand luggage check.
- security personnel informed by the database DB can clarify the situation with the traveler. All of this can happen without the traveler having to wait for identification.
- Expert knowledge for identification is stored as quantifiable and can therefore be used. Unlike with neural networks, the decision paths are mathematically traceable. The solution presented here is based on the feature space from which a feature vector is derived. Similar to a neural network or fuzzy logic, this is used as input and parameterized by weights to calculate a value for the likelihood of a person belonging to an identity.
- the MAC address can be used.
- the aggregation policy is a multi-level logic with fallback option, similar to a fuzzy logic approach.
- Weighted probabilities are processed.
- the weights are determined empirically to give particular weight to certain features (e.g., the face).
- the x are weak and could have arisen by guessing / random. 0.25: overall, the x gives a high probability of non-identification. 0.0: the person is with 100% certainty not the traveler to be identified. According to the rules, the following constellation arises for the example:
- the analysis and processing of the data may look like this, for example:
- an identification can still be made with a certain probability even if the face is covered during a subsequent detection of the traveler, thus, for example:
- Facial features Barely visible 0.1 1 0.1 Hair color medium brown 1 0.5 0.5
- weighting is only an example here. For example, if 0.75 is defined as the threshold, security personnel will be informed as a control instance, and if necessary. carried out a manual verification or identification of the traveler.
- FIGURE is diagrammatic, with essential properties and effects being shown, in part, significantly enlarged, in order to illustrate the functions, operating principles, technical configurations and features.
- every mode of operation, every principle, every technical embodiment and every feature which is / are disclosed in the figures or in the text, with all claims, every feature in the text and in the other figures, other modes of operation, principles, technical embodiments and features that are contained in this disclosure or arise from it, are freely and arbitrarily combined, so that all conceivable combinations of the described system are assigned.
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- Engineering & Computer Science (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Collating Specific Patterns (AREA)
- Alarm Systems (AREA)
Abstract
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE102017009430.6A DE102017009430B4 (de) | 2017-10-11 | 2017-10-11 | System zur Kontrolle einer Person |
PCT/EP2018/076973 WO2019072672A1 (fr) | 2017-10-11 | 2018-10-04 | Système de contrôle d'une personne |
Publications (1)
Publication Number | Publication Date |
---|---|
EP3695388A1 true EP3695388A1 (fr) | 2020-08-19 |
Family
ID=63787958
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP18782729.0A Pending EP3695388A1 (fr) | 2017-10-11 | 2018-10-04 | Système de contrôle d'une personne |
Country Status (5)
Country | Link |
---|---|
US (1) | US11195361B2 (fr) |
EP (1) | EP3695388A1 (fr) |
CN (1) | CN111316335A (fr) |
DE (1) | DE102017009430B4 (fr) |
WO (1) | WO2019072672A1 (fr) |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
GB2500823B (en) * | 2013-03-28 | 2014-02-26 | Paycasso Verify Ltd | Method, system and computer program for comparing images |
JP7327515B2 (ja) * | 2020-01-07 | 2023-08-16 | 日本電気株式会社 | ゲート装置、サーバ装置、出入国審査システム、ゲート装置の制御方法及びサーバ装置の制御方法 |
Family Cites Families (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2006029639A1 (fr) | 2004-09-13 | 2006-03-23 | Sita Information Networking Computing N.V. | Procede et systeme permettant l'accomplissement d'une procedure d'enregistrement, generateur de document d'identite et progiciel |
DE102004048403A1 (de) | 2004-10-01 | 2006-04-06 | Kaba Gallenschütz GmbH | Zugangskontrollvorrichtung |
US20100164680A1 (en) * | 2008-12-31 | 2010-07-01 | L3 Communications Integrated Systems, L.P. | System and method for identifying people |
DE102010016098A1 (de) | 2010-03-23 | 2011-09-29 | Kaba Gallenschütz GmbH | Zugangskontrollvorrichtung |
DE102012203313A1 (de) * | 2012-03-02 | 2013-09-05 | Bundesdruckerei Gmbh | Verfahren zum Identifizieren einer Person |
DE102012203311A1 (de) | 2012-03-02 | 2013-09-05 | Bundesdruckerei Gmbh | Verfahren zum Identifizieren einer Person |
FR3007171B1 (fr) | 2013-06-14 | 2019-08-23 | Idemia Identity And Security | Procede de controle de personnes et application a l'inspection des personnes |
US9773364B2 (en) * | 2014-07-28 | 2017-09-26 | Dan Kerning | Security and public safety application for a mobile device with audio/video analytics and access control authentication |
US9865144B2 (en) * | 2014-08-19 | 2018-01-09 | Sensormatic Electronics, LLC | Video recognition in frictionless access control system |
AU2015215965B2 (en) * | 2014-08-25 | 2016-12-22 | Accenture Global Services Limited | Secure short-distance-based communication and access control system |
AU2015358535B2 (en) * | 2014-12-02 | 2020-06-18 | Sensormatic Electronics Llc | Dual level human identification and location system |
US10275587B2 (en) * | 2015-05-14 | 2019-04-30 | Alclear, Llc | Biometric ticketing |
DE102015108330A1 (de) | 2015-05-27 | 2016-12-01 | Bundesdruckerei Gmbh | Elektronisches Zugangskontrollverfahren |
US11538126B2 (en) * | 2015-07-30 | 2022-12-27 | The Government of the United States of America, as represented by the Secretary of Homeland Security | Identity verification system and method |
DE102015010184A1 (de) * | 2015-08-11 | 2017-02-16 | Veridos Gmbh | Verfahren und Vorrichtung zur Durchführung einer Personenkontrolle |
-
2017
- 2017-10-11 DE DE102017009430.6A patent/DE102017009430B4/de active Active
-
2018
- 2018-10-04 EP EP18782729.0A patent/EP3695388A1/fr active Pending
- 2018-10-04 US US16/755,126 patent/US11195361B2/en active Active
- 2018-10-04 WO PCT/EP2018/076973 patent/WO2019072672A1/fr active Search and Examination
- 2018-10-04 CN CN201880070199.1A patent/CN111316335A/zh active Pending
Also Published As
Publication number | Publication date |
---|---|
WO2019072672A1 (fr) | 2019-04-18 |
DE102017009430A1 (de) | 2019-04-11 |
CN111316335A (zh) | 2020-06-19 |
US11195361B2 (en) | 2021-12-07 |
US20200320813A1 (en) | 2020-10-08 |
DE102017009430B4 (de) | 2024-04-25 |
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