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`mA
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`"s'n62rrtl
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`Old
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`UTILITY
`PATENT APPLICATION
`TRANSMITTAL
`
`ee i
`
`PTO/SB/05 Revised (11-00)
`
`37112-175340
`
`Attorney Docket No.
`First Inventor
`
`Alan J. LIPTON
`
`VIDEO SURVEILLANCE SYSTEM EMPLOYING
`VIDEO PRIMITIVES
`
`(Only for new nonprovisional applications under 37 C.F.R. 1.83/b})
`
`Express Mail Label No.
`
`APPLICATION ELEMENTS
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`1.04
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`Assistant Commissioner for Patents
`Box Patent Application
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`7.) CD-ROM or CD-R in duplicate, large table or
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`8. Nucleotide and/or Amino Acid Sequence Submission
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`a. (J Computer Readable Form (CRF)
`.
`b. Specification Sequence Listing on:
`i. J CD-ROM or CD-R (2 copies); or
`ii. () paper
`c. C] Statements verifying identity of above copies
`ACCOMPANYING APPLICATIONS PARTS
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`202-962-8300
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`2 3
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`
`:
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`(oreferred arrangementset forth below)
`~ Descriptive title of the Invention
`- Cross References to Related Applications
`- Statement Regarding Fed sponsored R&D
`- Reference to sequencelisting, a table,
`or a computerprogram listing appendix
`- Backgroundof the Invention
`- Brief Summary of the Invention
`- Brief Description of the Drawings( iffiled)
`- Detailed Description
`- Claim(s)
`- Abstract of the Disclosure
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`
`Assignment Papers (cover sheet & document(s)}
`37 C.F.R.§3.73(b) Statement
`[[] Powerof
`(when there is an assignee)
`Attorney
`wo English Transiation Document(if applicable)
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`{Should be specifically itemized)
`(for a continuation/divisional with Box 18 completed)
`15.)—Certified Copyof Priority Document(s)
`i] DELETION OF INVENTOR(S)
`(if foreign priority is claimed)
`Signed statement attached deleting inventor(s)
`Requestand Certification under 35 U.S.C. 122
`named in the prior application, see 37 CFR
`{o}(2)(B)(i). Applicant must attach form PTO/SB/35
`1.63(d){(2) and 1.33(b).
`or its equivalent.
`6.o1 Application Data Sheet. See 37 CFR 1.76
`Other:
`
`9.0]
`10.)
`
`16.
`
`17.0)
`
`6a. Priority is claimed underthe provisions of 35 U.S.C. § 120
`Appln No. 09/694.,712 filed on October 24. 2000.
`Appin No.
`filed in
`on
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`18. If a CONTINUING APPLICATION, check appropriate box, and supply the requisite information below andin a preliminary amendment,
`or in an Application Data Sheet under 37 CFR 1.76:
`0 Continuation
`O Divisional
`of prior application No: 09 /694,712
`Group /Art Unit:
`Prior application information:
`Examiner
`For CONTINUATION or DIVISIONAL APPSonly: The entire disclosure of the prior application, from which an oath or declaration is supplied
`under Box 5h,is considered a part of the disclosure of the accompanyingordivisional application and is hereby incorporated by reference.
`| The incorporation can only be relied upon when a portion has been inadvertently omitted from the submitted application parts.
`
`
`po20,ADDRESSGORRESPONDENCE
`20. CORRESPONDENCE ADDRESS
`veoevwcnnMMOIRT
`= ee
`
`Continuation-in-part (CIP)
`
`26694
`
`wnees PATENTTRADEMARK OFFICEoo see enon
`
`Name
`
`VENABLE
`
`Address|P.O. Box 34385
`
`Washington
`D.C. 20043-9998 Zip Code
`
`202-962-4800
`
`U.S.A
`
`Telephone
`
`
`
`Name (Print/Type)
`
`Michael A. Sartori, Ph.D.
`
`#332195 v1 - 37112-175340 - New App. Transmittal for C-I-P (DIAMONDBACK)
`PC Dots No. 332195
`
`J
`REUEANERE AT Lae
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`AVIGILON EX. 2007
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`Revised PTO/SB/35 (11-00)
`Approvedfor use through 10/31/2002 OMB 0651-0031
`U.S. Patent and Trademark Office; U. S. DEPARTMENT OF COMMERCE
`Underthe Paperwork Reduction Act of 1995, no persons are required to respondto a collection of information unlessit displays a valid OMB control number.
`Attorney Docket No. 332238
`
`
`
`
`
`
`
`
`
`
`First Named Inventor|Alan J. LIPTON
`
`
`REQUEST AND CERTIFICATION
`LLANCE SYSTEM EMPLOYING
`VIDEO SURVEI
`UNDER
`VES
`
`
`
`Title|VIDEO PRIMITI
`35 U.S.C. 122(b)(2)(B)(i)
`
`
`
`| hereby certify that the invention disclosed in the attached application has not and will not be
`
`the subject of an application filed in another country, or under a multilateral agreement, that
`
`requires publication at eighteen monthsafterfiling.| hereby requestthat the attached application
`not be published under 35 U.S.C. 122(b).
`
`
`
`Mpyerbu. (5, 208/
`
`Signature
`Date
`
`Michael A. Sartori, Ph.D. Reg. No. 41,289
`
`
`
` This request must be signed in compliance with 37 CFR 1.33(b) and submitted
`
`
`Applicant may rescind this nonpublication request at any time.
`If applicant
`rescinds a request that an application not be published under 35 U.S.C. 122(b),
`the application will be scheduled for publication at eighteen months from the
`earliest claimedfiling date for which a benefit is claimed.
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`Typed or printed name
`
`with the application uponfiling.
`
`lf applicant subsequentlyfiles an application directed to the invention disclosed in
`the attached application in another country, or under a multilateral international
`agreement, that requires publication of applications eighteen monthsafterfiling,
`the applicant mustnotify the United States Patent and Trademark Office of such
`filing within forty-five (45) days after the date of the filing of such foreign or
`international application. Failure to do so will result in abandonment of this
`application (35 U.S.C. 122(b)(2)(B)(iii)).
`
`
`
`SEND TO:Assistant Commissionerfor Patents, Washington, DC 20231.
`PC Docs No. 332238
`
`ARVOGRMEES ST LAR
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`APPLICATION FOR UNITED STATES PATENT
`
`
`
`INVENTORS:
`
`ALAN J. LIPTON
`THOMASM. STRAT
`PETER L. VENETIANER
`MARK C. ALLMEN
`WILLIAM E. SEVERSON
`NIELS HAERING
`ANDREW J. CHOSAK.
`ZHONG ZHANG
`MATTHEWF. FRAZIER
`JAMESS. SFEKAS
`TASUKI HIRATA
`JOHN CLARK
`
`TITLE:
`
`VIDEO SURVEILLANCE SYSTEM EMPLOYING
`VIDEO PRIMITIVES
`
`ATTORNEYS' ADDRESS:
`
`VENABLE
`1201 New York Avenue, N.W., Suite 1000
`Washington, D.C. 20005-3917
`Telephone: (202) 962-4800
`Telefax: (202) 962-8300
`
`ADDRESSFOR U.S.P.T.O. CORRESPONDENCE:
`
`VENABLE
`Post Office Box 34385
`Washington, D.C. 20043-9998
`
`ATTORNEY DOCKET NO.:
`
`37112-175340
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`VIDEO SURVEILLANCE SYSTEM EMPLOYING VIDEO PRIMITIVES
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`CROSS-REFERENCE TO RELATED APPLICATIONS
`
`[1]
`
`This application claimsthepriority of U.S. Patent Application No. 09/694,712
`
`filed October 24, 2000, which is incorporated herein by reference.
`
`BACKGROUND OF THE INVENTION
`
`Field of the Invention
`
`[2]
`
`The invention relates to a system for automatic video surveillance employing
`
`video primitives.
`
`References
`
`[3]
`
`For the convenienceofthe reader, the references referred to herein are listed
`
`below. In the specification, the numerals within brackets refer to respective references. The
`
`listed references are incorporated herein by reference.
`
`[4]
`
`[5]
`
`The following references describe movingtarget detection:
`
`{1} A. Lipton, H. Fujiyoshi andR.S. Patil, “Moving Target Detection and
`
`Classification from Real-Time Video,” Proceedings of IEEE WACV °98, Princeton, NJ, 1998,
`
`
`
`
`pp. 8-14.
`
`20
`
`[6]
`
`{2} W.ELL. Grimson,et al., “Using Adaptive Tracking to Classify and Monitor
`
`Activities in a Site”, CVPR, pp. 22-29, June 1998.
`
`[7]
`
`{3} A.J. Lipton, H. Fujiyoshi, R.S. Patil, “Moving Target Classification and
`
`Tracking from Real-time Video,” IUW,pp. 129-136, 1998.
`
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`[8]
`
`{4} T.J. Olson and F.Z.Brill, “Moving Object Detection and Event Recognition
`
`
`Algorithm for Smart Cameras,” IUW,pp. 159-175, May 1997.
`
`[9]
`
`The following references describe detecting and tracking humans:
`
`[10]
`
`{5} A.J. Lipton, “Local Application of Optical Flow to Analyse Rigid Versus
`
`Non-Rigid Motion,” International Conference on Computer Vision, Corfu, Greece, September
`
`1999.
`
`
`
`
`[11]
`
`{6} F. Bartolini, V. Cappellini, and A. Mecocci, “Counting people getting in and
`
`
`out of a bus by real-time image-sequenceprocessing,” IVC, 12(1):36-41, January 1994.
`
`[12]
`
`{7} M.Rossi and A. Bozzoli, “Tracking and counting moving people,” ICIP94,
`
`pp. 212-216, 1994.
`
`[13]
`
`{8} C.R. Wren, A. Azarbayejani, T. Darrell, and A. Pentland, “Pfinder: Real-
`
`time tracking of the human body,” Vismod, 1995.
`
`[14]
`
`{9} L. Khoudour, L. Duvieubourg,J.P. Deparis, “Real-Time Pedestrian Counting
`
`by Active Linear Cameras,” JEI, 5(4):452-459, October 1996.
`
`[15]
`
`{10} S. Ioffe, D.A. Forsyth, “Probabilistic Methods for Finding People,” IJCV,
`
`43(1):45-68, June 2001.
`
`[16]
`
`{11} M. Isard and J. MacCormick, “BraMBLe: A Bayesian Multiple-Blob
`
`Tracker,” ICCV,2001.
`
`[17]
`
`The following references describe blob analysis:
`
`20
`
`[18]
`
`{12} D.M.Gavrila, “The Visual Analysis of Human Movement: A Survey,”
`
`CVIU, 73(1):82-98, January 1999.
`
`[19]
`
`{13} Niels Haering and Niels da Vitoria Lobo, “Visual Event Detection,” Video
`
`Computing Series, Editor Mubarak Shah, 2001.
`
`-2-
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`(371 12-175340)
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`[20]
`
`[21]
`
`The following references describe blob analysis for trucks, cars, and people:
`
`{14} Collins, Lipton, Kanade, Fujiyoshi, Duggins, Tsin, Tolliver, Enomoto, and
`
`Hasegawa, "A System for Video Surveillance and Monitoring: VSAM Final Report," Technical
`
`Report CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon University, May 2000.
`
`[22]
`
`{15} Lipton, Fujiyoshi, and Patil, “Moving Target Classification and Tracking
`
`from Real-time Video,” 98 Darpa IUW,Nov. 20-23, 1998.
`
`[23]
`
`[24]
`
`The following reference describes analyzing a single-person blobandits contours:
`
`{16} C.R. Wren, A. Azarbayejani, T. Darrell, and A.P. Pentland. “Pfinder: Real-
`
`Time Tracking of the Human Body,” PAMI,vol 19, pp. 780-784, 1997.
`
`[25]
`
`The following reference describes internal motion ofblobs, including any motion-
`
`based segmentation:
`
`[26]
`
`{17} M. Allmen and C.Dyer, “Long--Range Spatiotemporal Motion
`
`Understanding Using Spatiotemporal Flow Curves,” Proc. IEEE CVPR, Lahaina, Maui, Hawaii,
`
`pp. 303-309, 1991.
`
`[27]
`
`{18} L. Wixson,"Detecting Salient Motion by Accumulating Directionally
`
`Consistent Flow", IEEE Trans. Pattern Anal. Mach.Intell., vol. 22, pp. 774-781, Aug, 2000.
`
`
`
`
`Backgroundof the Invention
`
`[28] Video surveillance of public spaces has become extremely widespread and
`
`20
`
`accepted by the general public. Unfortunately, conventional video surveillance systems produce
`
`such prodigious volumesofdata that an intractable problem results in the analysis of video
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`surveillance data.
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`[29]
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`A need exists to reduce the amountof video surveillance data so analysis of the
`
`video surveillance data can be conducted.
`
`[30] A need exists to filter video surveillance data to identify desired portions of the
`
`video surveillance data.
`
`
`
`
`SUMMARYOF THE INVENTION
`
`[31] An object of the invention is to reduce the amountof video surveillance data so
`
`analysis of the video surveillance data can be conducted.
`
`[32] An object of the inventionisto filter video surveillance data to identify desired
`
`portions of the video surveillance data.
`
`[33] An object of the invention is to produce a real time alarm based on an automatic
`
`detection of an event from video surveillance data.
`
`[34] An object of the invention is to integrate data from surveillance sensors other than
`
`video for improved searching capabilities.
`
`[35] An object of the inventionis to integrate data from surveillance sensors other than
`
`video for improved event detection capabilities
`
`[36]
`
`The invention includesan article of manufacture, a method, a system, and an
`
`apparatus for video surveillance.
`
`[37]
`
`The article of manufacture of the invention includes a computer-readable medium
`
`20
`
`comprising software for a video surveillance system, comprising code segments for operating the
`
`video surveillance system based on video primitives.
`
`[38]
`
`The article ofmanufacture of the invention includes a computer-readable medium
`
`comprising software for a video surveillance system, comprising code segments for accessing
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`archived video primitives, and code segments for extracting event occurrences from accessed
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`archived video primitives.
`
`[39]
`
`The system of the invention includes a computer system including a computer-
`
`readable medium having software to operate a computer in accordance with the invention.
`
`[40]
`
`The apparatus of the invention includes a computer including a computer-readable
`
`medium having software to operate the computer in accordance with the invention.
`
`[41]
`
`The article of manufacture of the invention includes a computer-readable medium
`
`having software to operate a computer in accordance with the invention.
`
`[42] Moreover, the above objects and advantages ofthe inventionare illustrative, and
`
`not exhaustive, ofthose that can be achieved by the invention. Thus, these and other objects and
`
`advantages of the invention will be apparent from the description herein, both as embodied
`
`herein and as modified in view of any variations which will be apparent to those skilled in the
`
`art.
`
`Definitions
`
`
`
`
`[43] A “video”refers to motion pictures represented in analog and/or digital form.
`
`Examplesof video include: television, movies, image sequences from a video cameraor other
`
`observer, and computer-generated image sequences.
`
`[44] A “frame”refers to a particular image or other discrete unit within a video.
`
`20
`
`[45] An “object” refers to an item of interest in a video. Examples of an object
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`include: a person, a vehicle, an animal, and a physical subject.
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`[46] An “activity” refers to one or more actions and/or one or more composites of
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`actions of one or more objects. Examples of an activity include: entering; exiting; stopping;
`
`moving; raising; lowering; growing; and shrinking.
`
`[47] A “location”refers to a space where an activity may occur. A location can be, for
`
`example, scene-based or image-based. Examples of a scene-based location include: a public
`
`space; a store; a retail space; an office; a warehouse; a hotel room; a hotel lobby; a lobby of a
`
`building; a casino; a busstation; a train station; an airport; a port; a bus; a train; an airplane; and
`
`a ship. Examples of an image-based location include: a video image;a line in a video image; an
`
`area in a video image; a rectangular section of a video image; and a polygonal section of a video
`
`image.
`
`[48] An “event” refers to one or more objects engaged in an activity. The event may
`
`be referenced with respect to a location and/or a time.
`
`[49] A “computer” refers to any apparatus that is capable of accepting a structured
`
`input, processing the structured input accordingto prescribed rules, and producingresults of the
`
`processing as output. Examples of a computer include: a computer; a general purpose computer;
`
`a supercomputer; a mainframe; a super mini-computer; a mini-computer; a workstation; a micro-
`
`computer; a server; an interactive television; a hybrid combination of a computer and an
`
`interactive television; and application-specific hardware to emulate a computer and/or software.
`
`A computer can have a single processor or multiple processors, which can operatein parallel
`
`
`
`20
`
`and/or notin parallel. A computer also refers to two or more computers connected together via a
`
`network for transmitting or receiving information between the computers. An example of such a
`
`computer includesa distributed computer system for processing information via computers
`
`linked by a network.
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`[50] A “computer-readable medium”refers to any storage device used for storing data
`
`accessible by a computer. Examples of a computer-readable medium include: a magnetic hard
`
`disk; a floppy disk; an optical disk, such as a CD-ROM and a DVD;a magnetic tape; a memory
`
`chip; and a carrier wave used to carry computer-readable electronic data, such as those used in
`
`transmitting and receiving e-mail or in accessing a network.
`
`[51]
`
`“Software”refers to prescribed rules to operate a computer. Examples of
`
`software include: software; code segments; instructions; computer programs; and programmed
`
`logic.
`
`[52] A “computer system” refers to a system having a computer, where the computer
`
`comprises a computer-readable medium embodying software to operate the computer.
`
`[53] A “network”refers to a number of computers and associated devices that are
`
`connected by communication facilities. A network involves permanent connections such as
`
`cables or temporary connections such as those made through telephone or other communication
`
`links. Examples of a network include: an internet, such as the Internet; an intranet; a local area
`
`network (LAN); a wide area network (WAN); and a combination of networks, such as an internet
`
`and an intranet.
`
`
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`[54]
`
`Embodiments ofthe invention are explained in greater detail by way ofthe
`
`20
`
`drawings, where the same reference numerals refer to the same features.
`
`[55]
`
`Figure 1 illustrates a plan view ofthe video surveillance system of the invention.
`
`[56]
`
`Figure 2 illustrates a flow diagram forthe video surveillance system of the
`
`invention.
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`“7-
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`[57]
`
`Figure 3 illustrates a flow diagram for tasking the video surveillance system.
`
`[58]
`
`Figure 4 illustrates a flow diagram for operating the video surveillance system.
`
`[59]
`
`Figure 5 illustrates a flow diagram for extracting video primitives for the video
`
`surveillance system.
`
`[60]
`
`Figure6 illustrates a flow diagram for taking action with the video surveillance
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`system.
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`
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`[61] Figure7illustrates a flow diagram for semi-automatic calibration of the video
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`surveillance system.
`
`[62]
`
`Figure8 illustrates a flow diagram for automatic calibration of the video
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`surveillance system.
`
`[63]
`
`Figure 9 illustrates an additional flow diagram for the video surveillance system
`
`of the invention.
`
`[64]
`
`Figures 10-15 illustrate examples of the video surveillance system of the
`
`invention applied to monitoring a grocery store.
`
`
`
`
`DETAILED DESCRIPTION OF THE INVENTION
`
`[65]
`
`The automatic video surveillance system of the invention is for monitoring a
`
`location for, for example, market research or security purposes. The system can be a dedicated
`
`video surveillance installation with purpose-built surveillance components,or the system can be
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`20
`
`a retrofit to existing video surveillance equipmentthat piggybacksoff the surveillance video
`
`feeds. The system is capable of analyzing video data from live sources or from recorded media.
`
`The system can have a prescribed responseto the analysis, such as record data, activate an alarm
`
`mechanism, or active another sensor system. The system is also capable of integrating with
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`-8-
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`(
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`other surveillance system components. The system produces security or market research reports
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`that can be tailored according to the needs of an operator and, as an option, can be presented
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`through an interactive web-based interface, or other reporting mechanism.
`
`[66] An operator is provided with maximum flexibility in configuring the system by
`
`using event discriminators. Event discriminators are identified with one or more objects (whose
`
`descriptions are based on video primitives), along with one or more optionalspatial attributes,
`
`and/or one or more optional temporalattributes. For example, an operator can define an event
`
`discriminator(called a "loitering" event in this example) as a “person” object in the “automatic
`
`teller machine” space for “longer than 15 minutes” and “between 10:00 p.m. and 6:00 a.m.”
`
`[67] Although the video surveillance system of the invention draws on well-known
`
`computer vision techniques from the public domain, the inventive video surveillance system has
`
`several unique and novel features that are not currently available. For example, current video
`
`surveillance systems use large volumesof video imagery as the primary commodity of
`
`information interchange. The system of the invention uses video primitives as the primary
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`commodity with representative video imagery being used as collateral evidence. The system of
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`the invention can also be calibrated (manually, semi-automatically, or automatically) and
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`thereafter automatically can infer video primitives from video imagery. The system can further
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`analyze previously processed video without needing to reprocess completely the video. By
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`analyzing previously processed video, the system can perform inference analysis based on
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`previously recorded video primitives, which greatly improvesthe analysis speed of the computer
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`system.
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`[68] As another example, the system of the invention provides unique system tasking.
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`Using equipment control directives, current video systemsallowauserto position video sensors
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`and, in some sophisticated conventional systems, to mask out regionsofinterest or disinterest.
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`Equipmentcontrol directives are instructions to control the position, orientation, and focus of
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`video cameras. Instead of equipment control directives, the system of the invention uses event
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`discriminators based on video primitives as the primary tasking mechanism. With event
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`discriminators and video primitives, an operator is provided with a much moreintuitive approach
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`over conventional systems for extracting useful information from the system. Rather than
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`tasking a system with an equipment control directives, such as “camera A pan 45 degrees to the
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`left,” the system of the invention can be tasked in a human-intuitive manner with one or more
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`event discriminators based on video primitives, such as “a person enters restricted area A.”
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`[69] Using the invention for market research, the following are examples of the type of
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`video surveillance that can be performed with the invention: counting people in a store; counting
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`people in a part of a store; counting people whostop in a particular place in a store; measuring
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`how long people spendin a store; measuring how long people spendin a part of a store; and
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`[70] Using the invention for security, the following are examplesofthe type of video
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`surveillance that can be performed with the invention: determining when anyoneenters a
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`restricted area and storing associated imagery; determining when a person enters an area at
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`unusual times; determining when changesto shelf space and storage space occur that might be
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`unauthorized; determining when passengers aboard an aircraft approach the cockpit; determining
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`measuring the length of a line inastore.
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`when peopletailgate through a secure portal; determining if there is an unattended bag in an
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`airport; and determiningif there is a theft of an asset.
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`[71]
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`Figure 1 illustrates a plan view ofthe video surveillance system of the invention.
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`A computer system 11 comprises a computer 12 having a computer-readable medium 13
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`embodying software to operate the computer 12 according to the invention. The computer
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`system 11 is coupled to one or more video sensors 14, one or more video recorders 15, and one
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`or more input/output(I/O) devices 16. The video sensors 14 can also be optionally coupled to
`the video recorders 15 for direct recording ofvideo surveillance data. The computer system is
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`optionally coupled to other sensors 17.
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`[72]
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`The video sensors 14 provide source video to the computer system 11. Each
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`video sensor 14 can be coupled to the computer system 11 using, for example, a direct
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`connection(e.g., a firewire digital camera interface) or a network. The video sensors 14 can
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`exist prior to installation of the invention or can beinstalled as part of the invention. Examples
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`of a video sensor 14 include: a video camera;a digital video camera; a color camera; a
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`monochrome camera; a camera; a camcorder, a PC camera; a webcam; an infra-red video
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`camera; and a CCTV camera.
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`[73]
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`The video recorders 15 receive video surveillance data from the computer system
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`11 for recording and/or provide source video to the computer system 11. Each video recorder 15
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`can be coupled to the computer system 11 using, for example, a direct connection or a network.
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`The video recorders 15 can exist prior to installation of the invention or can be installed as part
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`of the invention. Examplesof a video recorder 15 include: a video tape recorder; a digital video
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`recorder; a video disk; a DVD; and a computer-readable medium.
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`[74]
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`The I/O devices 16 provide input to and receive output from the computer system
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`11. The I/O devices 16 can be used to task the computer system 11 and produce reports from the
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`computer system 11. Examples of I/O devices 16 include: a keyboard; a mouse; a stylus; a
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`monitor; a printer; another computer system; a network; and an alarm.
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`[75]
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`The other sensors 17 provide additional input to the computer system 11. Each
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`other sensor 17 can be coupled to the computer system 11 using, for example, a direct connection
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`or anetwork. The other sensors 17 can exit prior to installation of the invention or can be
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`installed as part of the invention. Examples of another sensor 17 include: a motion sensor; an
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`optical tripwire; a biometric sensor; and a card-based or keypad-based authorization system. The
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`outputs of the other sensors 17 can be recorded by the computer system 11, recording devices,
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`and/or recording systems.
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`[76] Figure2illustrates a flow diagram for the video surveillance system of the
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`invention. Various aspects of the invention are exemplified with reference to Figures 10-15,
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`whichillustrate examples of the video surveillance system of the invention applied to monitoring
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`a grocery store.
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`[77]
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`In block 21, the video surveillance system is set up as discussed for Figure1.
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`Each video sensor 14 is orientated to a location for video surveillance. The computer system 11
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`is connected to the video feeds from the video equipment 14 and 15. The video surveillance
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`system can be implemented using existing equipment or newly installed equipment for the
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`location.
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`[78]
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`In block 22, the video surveillance system is calibrated. Once the video
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`surveillance system is in place from block 21, calibration occurs. The result of block 22 is the
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`ability of the video surveillance system to determine an approximate absolute size and speed of a
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`particular object (e.g., a person) at various places in the video image provided by the video
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`sensor. The system can be calibrated using manualcalibration, semi-automatic calibration, and
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`automatic calibration. Calibration is further described after the discussion of block 24.
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`[79]
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`In block 23 of Figure 2, the video surveillance system is tasked. Tasking occurs
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`after calibration in block 22 and is optional. Tasking the video surveillance system involves
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`specifying one or more eventdiscriminators. Without tasking, the video surveillance system
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`operates by detecting and archiving video primitives and associated video imagery without
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`taking any action, as in block 45 in Figure 4.
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`[80]
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`Figure 3 illustrates a flow diagram for tasking the video surveillance system to
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`determine event discriminators. An event discriminatorrefers to one or more objects optionally
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`interacting with one or more spatial attributes and/or one or more temporal attributes. An event
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`discriminator is described in terms of video primitives. A video primitive refers to an observable
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`attribute of an object viewed in a video feed. Examples of video primitives include the
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`following: a classification; a size; a shape; a color; a texture; a position; a velocity; a speed; an
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`internal motion; a motion; a salient motion; a feature of a salient motion; a scene change; a
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`feature of a scene change; and a pre-defined model.
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`[81]
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` Acclassification refers to an identification of an object as belongingto a particular
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`category or class. Examples ofa classification include: a person;a dog; a vehicle; a police car;
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`an individual person; and a specific type of object.
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`[82] A size refers to a dimensionalattribute of an object. Examples of a size include:
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`large; medium; small; flat; taller than 6 feet; shorter than 1 foot; wider than 3 feet; thinner than 4
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`feet; about human size; bigger than a human; smaller than a human; about the size of a car; a
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`20
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`rectangle in an image with approximate dimensionsin pixels; and a number of image pixels.
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`[83]
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` Acolor refers to a chromatic attribute of an object. Examples of a color include:
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`white; black; grey; red; a range of HSV values; a range of YUV values; a range of RGB values;
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`an average RGB value; an average YUV value; and a histogram of RGB values.
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`[84]
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`A texture refers to a pattern attribute of an object. Examples of texture features
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`include:self-similarity; spectral power; linearity; and coarseness.
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`[85] An internal motion refers to a measure ofthe rigidity of an object. An example of
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`a fairly rigid object is a car, which does not exhibit a great amount of internal motion. An
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`example of a fairly non-rigid object is a person having swinging arms and legs, which exhibits a
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`great amountof internal motion.
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`[86] A motion refers to any motion that can be automatically detected. Examples of a
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`motion include: appearance of an object; disappearance of an object; a vertical movement of an
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`object; a horizontal movementof an object; and a periodic movementof an object.
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`[87] A salient motion refers to any motion that can be automatically detected and can
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`be tracked for some period of time. Such a moving object exhibits apparently purposeful
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`motion. Examples ofa salient motion include: moving from oneplace to another; and moving to
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`interact with another object.
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`[88] A feature of a salient motion refers to a property of a salient motion. Examples of
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`a feature of a salient motion include: a trajectory; a length of a trajectory in image space; an
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`approximate length of a trajectory in a three-dimensional representation of the environment; a
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`position of an object in image space as a function of time; an approximateposition of an object
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`in a three-dimensional representation of the environmentas a function of time; a duration of a
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`trajectory; a velocity (e.g., speed and direction) in image space; an approximatevelocity(e.g.,
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`20
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`speed and direction) in a three-dimensional representation of the environment; a duration of time
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`at a velocity; a change of velocity in image space; an approximate changeof velocity in a three-
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`dimensional representation of the environment; a duration of a change of velocity; cessation of
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`motion; and a duration of cessation of motion. A velocity refers to the speed and direction of an
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`object at a particular time. A trajectory refers a set of (position, velocity) pairs for an object for
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`as long as the object can be tracked or for a time period.
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`[89] A-scene change refers to any region of a scene that can be detected as changing
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`over a period of time. Examples of a scene changeinc