EP3652673A1 - Personenerkennung in bereichen mit eingeschränkter datenübertragung und datenverarbeitung - Google Patents
Personenerkennung in bereichen mit eingeschränkter datenübertragung und datenverarbeitungInfo
- Publication number
- EP3652673A1 EP3652673A1 EP18753339.3A EP18753339A EP3652673A1 EP 3652673 A1 EP3652673 A1 EP 3652673A1 EP 18753339 A EP18753339 A EP 18753339A EP 3652673 A1 EP3652673 A1 EP 3652673A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- image data
- person recognition
- unit
- faces
- recognition device
- 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.)
- Ceased
Links
- 230000005540 biological transmission Effects 0.000 title claims abstract description 32
- 238000012545 processing Methods 0.000 title claims abstract description 25
- 238000000034 method Methods 0.000 claims abstract description 41
- 238000001514 detection method Methods 0.000 claims abstract description 35
- 238000012544 monitoring process Methods 0.000 claims description 19
- 238000004590 computer program Methods 0.000 claims description 8
- 238000004891 communication Methods 0.000 claims description 3
- 101100495769 Caenorhabditis elegans che-1 gene Proteins 0.000 claims 1
- 230000008901 benefit Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000012806 monitoring device Methods 0.000 description 4
- 238000012546 transfer Methods 0.000 description 4
- 150000001768 cations Chemical class 0.000 description 2
- 230000001419 dependent effect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 230000001815 facial effect Effects 0.000 description 2
- 238000012552 review Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
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- 230000002349 favourable effect Effects 0.000 description 1
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- 238000011835 investigation Methods 0.000 description 1
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- 230000001681 protective effect Effects 0.000 description 1
- 230000035484 reaction time Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
Definitions
- the invention relates to a method for recognizing persons in an area with limited data transmission and data processing capabilities. Furthermore, the invention relates to a person recognition system. In addition, the invention relates to a transport system.
- Video data is used for evidence and for purposes of investigation and for real-time monitoring.
- an automated monitoring is increasingly used.
- passenger transport not only stationary railway systems and buildings but also vehicles are included in the recording and monitoring. With real-time monitoring and looking dangerous individuals are identified who ⁇ . Due to the limited bandwidth to the land side and because of lack of manual or personal resources in the vehicles, a manual monitoring in the vehicle is difficult.
- a landside recognition on the basis of image data recorded on the vehicle side is made more difficult by the low bandwidth of the data transmission from the vehicles.
- US 2010/0329568 Al identifying Perso ⁇ nen using stationary image recording units is described.
- US 2004/0 117 638 AI facial signatures are identified by means of image recordings of cameras for the purpose of recognizing persons.
- This object is achieved by a method for detection in an area with limited data transmission and Da ⁇ ten kausston according to claim 1, a passenger detection system according to claim 9 as well as a transport system according to claim 10 degrees.
- image data are acquired from the area to be monitored.
- An area of limited data transfer and processing capabilities is one where bandwidth for data transfer and computational power is significantly limited due to design or engineering constraints compared to traditional monitored areas, resulting in the transmission of large amounts of video data in real time is not possible in the area or into this area and processing of the acquired monitoring data, ie the image data, directly in or on the area to be monitored is not possible.
- faces are detected by means of an internal detection unit.
- Detection or recognition of faces in this context means that It is known in which image data faces occur without individual faces are identified, that are assigned to specific persons or identities.
- a detection unit which is located in or directly at the area to be monitored should be understood as an internal detection unit.
- an internal detection unit would be located in or on the vehicle and located in a driving ⁇ convincing.
- For the detection unit can to already available
- image data are selected in which faces were detected.
- the selected image data are transmitted to an external, stationary personal recognition device.
- the external person recognition device is located outside Outside of the area to be monitored and therefore is not subject to the restrictions that affect the bandwidth of data transmission and data processing.
- faces are identified on the basis of the selected image data.
- Identifi ⁇ ornamentation should be understood in this context that the individual faces identities of persons are assigned.
- the monitoring data in the area to be monitored are already greatly reduced by the described selection, so that the amount of data to be transmitted for the limited data transmission options is not a problem.
- the face recognition which takes place in or on the area to be monitored, requires ⁇ advantageous way of relatively low computing resources so that they can be handled there in real time.
- the actual identification process of the individual persons takes place before ⁇ geous in the external person recognition device, in the ideal case less or no relevant restrictions of the data processing resources are available, so that the identification of persons located in the area to be monitored can be done promptly or even in real time.
- timely protective measures or countermeasures can be taken so that In most cases, it does not even come to serious violent acts in the area to be monitored.
- the security is also guaranteed in areas in which a complete direct monitoring or evaluation of the monitoring data is not or only with difficulty possible.
- the area to be monitored is arranged in a transport vehicle and the external person recognition device is arranged stationary. That is to say, the image recording, the face recognition and the selection of the image data which have faces takes place in the transport vehicle and the actual identification of faces on the basis of the selected image data is carried out stationarily outside the transport vehicle.
- the pressure prevailing in the transport vehicle limited verarbei ⁇ processing capacity are used for a preselection of the detected in the transport vehicle image data advantageous, so that the to übertra ⁇ constricting amount of image data is reduced.
- the reduced image data amount is then transmitted via usually only be ⁇ limits in the transport vehicle or narrowband existing übertragungsein ⁇ units to the external stationary pedestrian recognition device, which then fills with extensive computing resources, the actual identification task ER.
- the person recognition system comprises an area to be monitored with limited data transmission and data processing capabilities.
- Part of the person recognition system according to the invention is also an internal person monitoring unit, which comprises an internal image recording unit for acquiring image data from the area to be monitored.
- the internal person monitoring unit also has an internal detection unit for detecting faces in the image data.
- Part of the internal josüberwachungs- unit is also an internal selection unit for Selektie ⁇ ren the image data in which faces have been detected, and an internal data communication unit for transmitting the selected image data to an external person recognition device.
- the personal identification system according to the invention also comprises an external person recognition device having an external data receiving unit for receiving the information provided by the internal data communication unit Rickda ⁇ th and an external person recognition unit for identifi ⁇ cation of faces on the basis of the selected image data using the external person recognition unit comprises.
- the person recognition system according to the invention shares the advantages of the method according to the invention for recognizing persons in an area to be monitored with limited data transmission and data processing possibilities.
- the transport system comprises at least one transport vehicle and at least one inventive Perso ⁇ nenerkennungssystem, wherein the transport vehicle ten kausève the area to be monitored with limited data transmission and data of the passenger detection system comprises.
- the transport vehicle may be, for example, a roads ⁇ vehicle, for meadow a bus, or a rail drive ⁇ generating, for meadow, a train, a train or a subway.
- the area to be monitored may be, for example, a passenger area or an area of a driver's cab.
- Personal monitoring unit of Congresser ⁇ detection system according to the invention is arranged in the transport vehicle.
- the Transport system according to the invention shares the advantages of the person recognition system according to the invention.
- Some components of the person recognition system according to the invention can for the most part be designed in the form of software components. This applies in particular to parts of the internal person monitoring unit and the external person recognition device . In principle, however, these components can also be partially realized, in particular when it comes to particularly fast calculations, in the form of software-supported hardware, for example FPGAs or the like. Likewise, the required interfaces, for example, if it is only about a transfer of data from other software components, be designed as software interfaces. But they can also be configured as hardware on ⁇ built interfaces which are controlled by appropriate software.
- a largely software implementation has the advantage that for monitoring a range existing computer systems can already far after a possible addition of extra hardware elements to easily be retrofitted by a software update to work on the OF INVENTION ⁇ dung contemporary way.
- the task also by a corresponding computer program product with a
- Computer program solved which is directly loadable into a memory device of such a computer system, with program sections ⁇ to perform all the steps of the inventive method when the computer program is executed in the computer nersystem.
- Such a computer program product in addition to the computer ⁇ program optionally additional components, such as documentation and / or additional components, including hardware components, such as hardware keys (dongles, etc.) for using the software.
- additional components such as documentation and / or additional components, including hardware components, such as hardware keys (dongles, etc.) for using the software.
- a computer-readable medium for example a memory stick, a hard disk or other transportable or permanently installed data carrier can be used, on which the program sections of the computer program which can be read and executed by a computer unit are stored are.
- the computer unit may be for example a purpose or more cooperating micropro ⁇ processors or the like.
- the detection of faces with a low non-detection rate and a high recognition rate is performed.
- the recognition rate is the rate at which something, in this case a face, is positively recognized as what is expected, ie in this case as a face.
- the non-recognition rate is the complement to it. Both rates are expected to ⁇ gether 100%.
- a low non-recognition rate should be understood as a rate of 10% or less, preferably 1% or less. For example, a high rate of false positives of faces may be tolerated. Because the internally selected image data represent only a preselection, which can then be edited in the external person recognition device.
- the lowest possible non-recognition rate makes it possible As well as all faces are captured or fed to the second stage of the person recognition process.
- image data which does not include any faces are sorted out in advance with the aid of the external person recognition device.
- the extent of the evaluated at a identifi ⁇ cation of persons on the basis of face data is reduced by the image data advantageously which do not contribute to Ge ⁇ face recognition.
- the method for personnel nenerkennung in the monitored area with limited data transmission and data processing capabilities of the identification process is completed by the Wunscherken ⁇ voltage device before starting the next breakpoint by the transport vehicle.
- the escape of a dangerous person can be prevented in good time, so that the safety for travelers is improved.
- the external person recognition device is designed as a central person recognition device.
- the personal recognition device receives image data selected by a plurality of areas to be monitored and evaluates them.
- the resources of the centra ⁇ len people detection device for monitoring several areas can, for example, several Transportfahrzeu ⁇ gen, be used simultaneously, so the cost of monitoring is advantageously reduced.
- the external person detection device uses an automated identification procedure.
- personnel can be saved in the identification and human carelessness errors can be avoided by the automated identification.
- the identification can be done with sufficient computing capacity in real time, so that the reaction time can be reduced to potential dangers.
- a manual identification process is connected downstream of the automated identification method.
- non-identifiable or incorrectly identified persons whose faces are mapped to the image data to be evaluated can be identified and, if necessary, corrected in identifying the person Persons are carried out. Consequently, a more accurate iden ⁇ tification of persons will be achieved in the area to be monitored.
- the invention will be explained in more detail below with reference to the beige ⁇ added figures using exemplary embodiments. Show it:
- FIG. 1 shows a flow chart illustrating a method for supervision chen the speed of a rail vehicle according to an embodiment of the invention illustrated light ⁇ ,
- FIG. 2 shows a block diagram which illustrates a speed-determining device according to an embodiment of the invention
- FIG. 3 is a block diagram illustrating light- ⁇ a rail vehicle according to an embodiment of the invention.
- FIG. 1 shows a flowchart 100 which illustrates a method for detecting persons in an area B to be monitored with limited data transmission and data processing options.
- image data BD from the area B, in this embodiment an interior area B of a rail vehicle 51 (see FIG. 3), is recorded.
- the image data BD can be taken, for example by means of a instal in the rail vehicle ⁇ profiled camera.
- step l.II faces in the image data BD are detected with the aid of an internal detection unit 32 integrated in the rail vehicle (see FIG. 2).
- the image data BD-G in which G faces have been detected, selected and in step 1.
- step IV includes those ⁇ selected image data BD-G to an external Wegerkennungsein- l.III direction 40 (see FIG 2) transmitted.
- the external person ⁇ detection device 40 is stationarily positioned outside of the rail vehicle 51. Since only the selected Stressda ⁇ th BD-G of the rail vehicle 51 to the stationary per- can be transmitted, the data transmission rate between the rail vehicle 51 and the stationary external person recognition device 40 may be relatively low.
- faces G are then identified on the basis of the selected image data BD-G with the aid of the external person recognition device 40.
- the person recognition system 20 includes an internal personal monitoring device 30 which is disposed for example in a rail vehicle 51, 52 (see FIG 3), and an external stationary Wegerken ⁇ drying apparatus 40.
- the internal personal monitoring device 30 comprises an image pickup unit 31, such as a camera 31 in that image data BD is recorded from an interior of the rail vehicle.
- the image data BD are continuously detected in an observation period, for example, moves while the rail vehicle between two holding points and are detected at an internal detection unit 32 via ⁇ averages, with the faces in the image data G BD.
- an automated detection method is used with which it is determined whether or not faces are present in an image. This simple step, which does not identify the Ge ⁇ classifier takes place, can be relatively low verarbei ⁇ maintenance effort in the rail vehicle in real time Runaway ⁇ leads.
- the internal detection unit 32 transmits information G to the facial images to an internal selection unit 33.
- the internal selection unit also receives the image data BD by the image pickup unit 31.
- the selection ⁇ unit 33 now searches the image data sets BD-G of the listed taken image data BD out in which 32 faces G detected by the detection unit.
- the selected image data BD-G are then exceeded over a radio unit 34 to be ⁇ already said external person recognition device 40 averages.
- the person recognition device 40 comprises a data reception unit 41 with which the image data BD-G, which faces G detected by the vehicle-side personal monitoring device 30, are received. 41, the selected image data BD-G are transmitted to a person recognition unit 42, which is also part of the stationary external ⁇ person identification device 40 from the DA tenempfangsaku.
- the person recognition unit 42 is set up to identify in the detected faces G in the selected image data BD-G, ie to assign it to specific persons.
- FIG 3 a block diagram is shown illustrating a transmembrane ⁇ port system 50 according to an embodiment of the invention.
- the transport system 50 comprises a plurality of rail vehicles 51, 52 which are traveling on track lines Gl, G2. Furthermore, the transport system 50 also includes a person recognition system 20. Parts of the transport system 20, namely the internal person monitoring devices 30, which are constructed as shown in FIG. 2, are arranged in the two rail vehicles 51, 52 and transmit radio-selected image data BD-G a stationary external person recognition device 40, which processes the selected image data BD in the manner described in connection with FIG. 1 and FIG.
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Human Computer Interaction (AREA)
- Image Analysis (AREA)
- Alarm Systems (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE102017215037 | 2017-08-29 | ||
PCT/EP2018/070835 WO2019042689A1 (de) | 2017-08-29 | 2018-08-01 | Personenerkennung in bereichen mit eingeschränkter datenübertragung und datenverarbeitung |
Publications (1)
Publication Number | Publication Date |
---|---|
EP3652673A1 true EP3652673A1 (de) | 2020-05-20 |
Family
ID=63174203
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP18753339.3A Ceased EP3652673A1 (de) | 2017-08-29 | 2018-08-01 | Personenerkennung in bereichen mit eingeschränkter datenübertragung und datenverarbeitung |
Country Status (2)
Country | Link |
---|---|
EP (1) | EP3652673A1 (de) |
WO (1) | WO2019042689A1 (de) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2023227351A1 (de) * | 2022-05-25 | 2023-11-30 | Siemens Mobility GmbH | Verfahren zum betreiben eines kamerasystems eines spurgebundenen fahrzeugs und system für ein spurgebundenes fahrzeug unter verwendung künstlicher intelligenz |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7634662B2 (en) | 2002-11-21 | 2009-12-15 | Monroe David A | Method for incorporating facial recognition technology in a multimedia surveillance system |
KR100778060B1 (ko) * | 2007-06-01 | 2007-11-21 | (주)텔릭스타 | 얼굴인식기술을 이용한 위난방지장치 및 이를 이용한위난방지장치 시스템 |
US8600121B2 (en) | 2008-07-02 | 2013-12-03 | C-True Ltd. | Face recognition system and method |
US9235750B1 (en) * | 2011-09-16 | 2016-01-12 | Lytx, Inc. | Using passive driver identification and other input for providing real-time alerts or actions |
US8744642B2 (en) * | 2011-09-16 | 2014-06-03 | Lytx, Inc. | Driver identification based on face data |
-
2018
- 2018-08-01 EP EP18753339.3A patent/EP3652673A1/de not_active Ceased
- 2018-08-01 WO PCT/EP2018/070835 patent/WO2019042689A1/de active Search and Examination
Non-Patent Citations (1)
Title |
---|
HJELMAS E ET AL: "Face Detection: A Survey", COMPUTER VISION AND IMAGE UNDERSTANDING, ACADEMIC PRESS, US, vol. 83, no. 3, 1 September 2001 (2001-09-01), pages 236 - 274, XP004434095, ISSN: 1077-3142, DOI: 10.1006/CVIU.2001.0921 * |
Also Published As
Publication number | Publication date |
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WO2019042689A1 (de) | 2019-03-07 |
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