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WO2008034780A1 - Procédé de surveillance de rassemblements de personnes - Google Patents

Procédé de surveillance de rassemblements de personnes Download PDF

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Publication number
WO2008034780A1
WO2008034780A1 PCT/EP2007/059750 EP2007059750W WO2008034780A1 WO 2008034780 A1 WO2008034780 A1 WO 2008034780A1 EP 2007059750 W EP2007059750 W EP 2007059750W WO 2008034780 A1 WO2008034780 A1 WO 2008034780A1
Authority
WO
WIPO (PCT)
Prior art keywords
persons
people
speed
comparison
day
Prior art date
Application number
PCT/EP2007/059750
Other languages
German (de)
English (en)
Inventor
Wolfram Klein
Gerta KÖSTER
Original Assignee
Siemens Aktiengesellschaft
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Siemens Aktiengesellschaft filed Critical Siemens Aktiengesellschaft
Priority to EP07803514A priority Critical patent/EP2064666A1/fr
Publication of WO2008034780A1 publication Critical patent/WO2008034780A1/fr

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
    • G07C11/00—Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats

Definitions

  • the invention relates to a method for monitoring the accumulation of persons according to the preamble of claim 1.
  • a sensor module detects the location coordinates of individual persons in a room to be monitored from entering to leaving.
  • a sensor module can serve a CCD camera.
  • means and methods or algorithms of the image processing are used to detect or identify the objects and subjects located in a room. From gray or color values and circumscribing shapes, the movement behavior of persons is derived according to position and speed.
  • a disadvantage of this prior art is that thereby no recognition of dangerous incidents or potentially developing dangerous situations is possible.
  • the monitoring area can not open to the imaging device, concealed subregions, de ⁇ ren additions are in the monitored area, and a review of the hidden sub-regions can based on comparison ⁇ patterns for the inflow and outflow through the entrances SUC ⁇ gen.
  • the comparison patterns for the subregions are dependent on the weather, the season, the time of day, the day of the week and / or the type of event.
  • a model for the behavior of the persons in the subregions is created for the evaluation, in which the subareas are assigned parameters depending on the weather, the season, the time of day, the day of the week and / or the type of event.
  • a better prognosis can be made for typical situations depending on circumstances such as time or weather.
  • the assessment will be more accurate in the event that many people leave a folk festival in the late evening in bad weather.
  • An accident can be detected by a comparison pattern in which the speed of individual persons within ei ⁇ nes flow of people is significantly lower and these move to a center and / or a circle without other people trained around this.
  • a panic situation is detected by a comparison pattern in which flows of people with high speed of movement, high density of people occur at the same time forming areas without or with a few people.
  • the gradient of the person density is evaluated.
  • the first and second Ablei ⁇ tion of the person density and / or the speed of movement of the people is evaluated.
  • the number of people in an area or subarea is a function of time and place. By comparing the positions of the persons at different times, the derivative of this function is determined by time or approximated by difference quotients.
  • the derivation according to the location (gradient) provides information about the local changes in the number of persons or persons (number of people / area). Even higher derivatives can be approximated by differential quotients.
  • the number of persons and the flows of persons can be predicted.
  • An evaluation is possible even if not all persons can be recorded. It is also possible to additionally include selected persons in order to obtain information about the distribution of certain groups of persons in the mass of persons. hold. This can be, for example, children or wheelchair users, who need a higher level of protection than other people. Such persons may be recognized by special markings such as a cap or cap, or physical characteristics such as height.
  • FIG. 1 is a schematic plan view of a monitoring area with subregions on the basis of the example of a Murphy ,
  • FIG. 2 schematically shows an assignment of parameters to subregions
  • Fig. 3B schematically shows a second comparison pattern for an accident
  • FIGS. 4A-4C schematically show the sequence of a comparison pattern for a panic situation.
  • FIG. 1 shows schematically in plan view a monitoring range 1 with subregions on the basis of the example of a popular event .
  • the persons are indicated by dots.
  • the gradient of the streams of people outside in the sub-area entrance beer tent 5 can be used as a guideline for determining the number of persons in the subarea beer tent 4.
  • the monitoring of the movement pattern allows an estimation of a development in a subsequent period.
  • FIG. 2 schematically shows an assignment of parameters to subregions.
  • the driving business 3 the beer tent 4, a roast chicken stand 9 and a Rie ⁇ senrad 10 are arranged.
  • typical properties are taken into account in the comparative samples.
  • Under section z as in areas that have normally gleichze ⁇ FLOWING persons distribution as the road section 2, only sparse with people under areas such as the roller coaster as
  • a concrete assessment and prognosis is described ⁇ model to allow for different scenarios, a Prog ⁇ nose of the distribution of people in sub-regions, starting from the current distribution people.
  • different parameters eg P (weather) and P (time), which are dependent on the respective sub-area and correspond to an "attractiveness" for persons under the parameter condition Scenarios and for the sub-area concerned.
  • the value range of the parameters is specified as [0,1].
  • FIG. 2 shows by way of example a parameterization with values P A for a-bends and at the same time P R for rain.
  • Fig. 3A schematically shows a comparative pattern for an accident.
  • the parties are shown as a point with an arrow on its movement direction and a movement speed ent ⁇ speaking arrow length.
  • Fig. 3B schematically shows a second comparison pattern for a possible accident. Around a few people, a circle without further people forms and the speed of the people in this circle is very low or zero.
  • FIGS. 4A-4C schematically show the timing of a comparison pattern for a panic situation.
  • critical masses, traps and accident patterns can either be recognized directly or predicted via extrapolation, eg a linear extrapolation of the movements. This can be used to respond appropriately, such as automatically triggering alerts, informing and enabling security services.
  • the monitoring can automatically focuses on the danger zone, where refined ⁇ to.
  • the threshold values are specified depending on which parameters (weather, time of day, etc.) are available.
  • the threshold values can be determined depending on a sub-range. For example, in a subway station at rush hour, higher person densities are tolerable than at 3 o'clock in the morning, when an accumulation of people may indicate a danger situation, such as a developing brawl.
  • the method according to the invention represents a control loop, ie the information obtained can be used directly for better detection in the next steps. When a crisis area detected automatically, for example by a threshold value, so in this region, the detection can be verfei ⁇ nert. Options include zooming in or special alignment of additional cameras. Next, additional data can be determined as to the density of the BEWE ⁇ transfer speed of persons as well as the uniformity and distribution of the speed of movement.
  • the reference patterns e.g. based on experience in the past, and the parameters are adjusted. Possible measures may be to block inputs and to only use them as an output, as well as further monitoring based on comparison patterns and parameters for the case of evacuation.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Alarm Systems (AREA)
  • Image Analysis (AREA)

Abstract

Selon le procédé selon l'invention de surveillance de rassemblements de personnes dans une zone de surveillance (1), les étapes suivantes sont répétées : prise de vue du rassemblement de personnes grâce à un dispositif de prise de vues, détection de la position d'une pluralité de personnes sur la vue grâce à un dispositif d'analyse, et comparaison avec les positions sur une vue précédente. Une direction et une vitesse sont alors respectivement attribuées par le dispositif d'analyse. Les positions, directions de déplacement et vitesses de déplacement des personnes obtenues sont comparées avec des modèles témoins pour une pluralité de personnes, en réalisant de la sorte une évaluation d'un événement en cours ou futur.
PCT/EP2007/059750 2006-09-20 2007-09-17 Procédé de surveillance de rassemblements de personnes WO2008034780A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP07803514A EP2064666A1 (fr) 2006-09-20 2007-09-17 Procédé de surveillance de rassemblements de personnes

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102006044298.9 2006-09-20
DE102006044298A DE102006044298B3 (de) 2006-09-20 2006-09-20 Verfahren zur Überwachung von Personenansammlungen

Publications (1)

Publication Number Publication Date
WO2008034780A1 true WO2008034780A1 (fr) 2008-03-27

Family

ID=38695575

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2007/059750 WO2008034780A1 (fr) 2006-09-20 2007-09-17 Procédé de surveillance de rassemblements de personnes

Country Status (3)

Country Link
EP (1) EP2064666A1 (fr)
DE (1) DE102006044298B3 (fr)
WO (1) WO2008034780A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103699874B (zh) * 2013-10-28 2017-04-12 中国计量学院 基于surf流和lle稀疏表示的人群异常行为识别方法

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2476500B (en) * 2009-12-24 2012-06-20 Infrared Integrated Syst Ltd Activity mapping system
DE102010034072A1 (de) * 2010-08-12 2012-02-16 Crosscan Gmbh Personenleitsystem für die Evakuierung eines Gebäudes oder eines Gebäudeabschnittes
DE102019123523A1 (de) * 2019-09-03 2021-03-04 Innogy Se Verfahren und Computerprogrammprodukt zum Bestimmen von Bewegungsströmen von Personen
JP7292532B1 (ja) 2022-04-27 2023-06-16 三菱電機株式会社 制御装置、制御システム、制御方法、及び制御プログラム

Citations (8)

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Publication number Priority date Publication date Assignee Title
WO1994027408A1 (fr) * 1993-05-14 1994-11-24 Rct Systems, Inc. Moniteur de trafic video pour surfaces de vente au detail et emplacements similaires
WO1998008208A2 (fr) * 1996-08-22 1998-02-26 Footfall Limited Systemes d'imagerie video
US5764283A (en) * 1995-12-29 1998-06-09 Lucent Technologies Inc. Method and apparatus for tracking moving objects in real time using contours of the objects and feature paths
US5953055A (en) * 1996-08-08 1999-09-14 Ncr Corporation System and method for detecting and analyzing a queue
US5973732A (en) * 1997-02-19 1999-10-26 Guthrie; Thomas C. Object tracking system for monitoring a controlled space
DE20015559U1 (de) * 1999-09-06 2001-01-11 Lausch, Holger, Dr., 07743 Jena Anordnung zur Erfassung von Personenströmen, Personen und Objekten und/oder zur Analyse des Rezeptionsverhaltens von Personen
US20040161133A1 (en) * 2002-02-06 2004-08-19 Avishai Elazar System and method for video content analysis-based detection, surveillance and alarm management
US20050169367A1 (en) * 2000-10-24 2005-08-04 Objectvideo, Inc. Video surveillance system employing video primitives

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4700295A (en) * 1985-04-18 1987-10-13 Barry Katsof System and method for forecasting bank traffic and scheduling work assignments for bank personnel
IL159828A0 (en) * 2004-01-12 2005-11-20 Elbit Systems Ltd System and method for identifying a threat associated person among a crowd

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1994027408A1 (fr) * 1993-05-14 1994-11-24 Rct Systems, Inc. Moniteur de trafic video pour surfaces de vente au detail et emplacements similaires
US5764283A (en) * 1995-12-29 1998-06-09 Lucent Technologies Inc. Method and apparatus for tracking moving objects in real time using contours of the objects and feature paths
US5953055A (en) * 1996-08-08 1999-09-14 Ncr Corporation System and method for detecting and analyzing a queue
WO1998008208A2 (fr) * 1996-08-22 1998-02-26 Footfall Limited Systemes d'imagerie video
US5973732A (en) * 1997-02-19 1999-10-26 Guthrie; Thomas C. Object tracking system for monitoring a controlled space
DE20015559U1 (de) * 1999-09-06 2001-01-11 Lausch, Holger, Dr., 07743 Jena Anordnung zur Erfassung von Personenströmen, Personen und Objekten und/oder zur Analyse des Rezeptionsverhaltens von Personen
US20050169367A1 (en) * 2000-10-24 2005-08-04 Objectvideo, Inc. Video surveillance system employing video primitives
US20040161133A1 (en) * 2002-02-06 2004-08-19 Avishai Elazar System and method for video content analysis-based detection, surveillance and alarm management

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103699874B (zh) * 2013-10-28 2017-04-12 中国计量学院 基于surf流和lle稀疏表示的人群异常行为识别方法

Also Published As

Publication number Publication date
EP2064666A1 (fr) 2009-06-03
DE102006044298B3 (de) 2008-01-31

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