WO2004034236A3 - Systems and methods for recognition of individuals using multiple biometric searches - Google Patents

Systems and methods for recognition of individuals using multiple biometric searches Download PDF

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Publication number
WO2004034236A3
WO2004034236A3 PCT/US2003/033073 US0333073W WO2004034236A3 WO 2004034236 A3 WO2004034236 A3 WO 2004034236A3 US 0333073 W US0333073 W US 0333073W WO 2004034236 A3 WO2004034236 A3 WO 2004034236A3
Authority
WO
WIPO (PCT)
Prior art keywords
biometric
predetermined portion
results set
individuals
recognition
Prior art date
Application number
PCT/US2003/033073
Other languages
French (fr)
Other versions
WO2004034236A2 (en
Inventor
James V Howard
Francis Frazier
Original Assignee
Digimarc Corp
James V Howard
Francis Frazier
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 Digimarc Corp, James V Howard, Francis Frazier filed Critical Digimarc Corp
Priority to AU2003282943A priority Critical patent/AU2003282943A1/en
Publication of WO2004034236A2 publication Critical patent/WO2004034236A2/en
Publication of WO2004034236A3 publication Critical patent/WO2004034236A3/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/243—Classification techniques relating to the number of classes
    • G06F18/24323—Tree-organised classifiers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/254—Fusion techniques of classification results, e.g. of results related to same input data
    • G06F18/256—Fusion techniques of classification results, e.g. of results related to same input data of results relating to different input data, e.g. multimodal recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G06V10/809—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data
    • G06V10/811—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data the classifiers operating on different input data, e.g. multi-modal recognition
    • 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
    • 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
    • G06V40/12—Fingerprints or palmprints
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/912—Applications of a database
    • Y10S707/913—Multimedia
    • Y10S707/915—Image

Abstract

The invention provides a computer-implemented method for determining whether a database contains any images that substantially match at least one image provided of an individual. A probe data set is received, the comprising first and second biometric templates associated with the individual, the first biometric template associated with a different type of biometric than the second type of biometric template. A database of biometric templates is searched using the first biometric template to retrieve a first results set. A first predetermined portion of the first results set is selected. The first predetermined portion of the first results set is searched using the second biometric template to retrieve a second results set. A second predetermined portion of the second results set is selected. The second predetermined portion of the second results is provided for comparison with the image provided of the individual.
PCT/US2003/033073 2002-10-11 2003-10-14 Systems and methods for recognition of individuals using multiple biometric searches WO2004034236A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2003282943A AU2003282943A1 (en) 2002-10-11 2003-10-14 Systems and methods for recognition of individuals using multiple biometric searches

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US41812902P 2002-10-11 2002-10-11
US60/418,129 2002-10-11
US42950102P 2002-11-26 2002-11-26
US60/429,501 2002-11-26

Publications (2)

Publication Number Publication Date
WO2004034236A2 WO2004034236A2 (en) 2004-04-22
WO2004034236A3 true WO2004034236A3 (en) 2005-02-24

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2003/033073 WO2004034236A2 (en) 2002-10-11 2003-10-14 Systems and methods for recognition of individuals using multiple biometric searches

Country Status (3)

Country Link
US (2) US7277891B2 (en)
AU (1) AU2003282943A1 (en)
WO (1) WO2004034236A2 (en)

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