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WO2003088131A3 - Method and apparatus for face description and recognition using high-order eigencomponents - Google Patents

Method and apparatus for face description and recognition using high-order eigencomponents Download PDF

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Publication number
WO2003088131A3
WO2003088131A3 PCT/JP2003/004550 JP0304550W WO03088131A3 WO 2003088131 A3 WO2003088131 A3 WO 2003088131A3 JP 0304550 W JP0304550 W JP 0304550W WO 03088131 A3 WO03088131 A3 WO 03088131A3
Authority
WO
WIPO (PCT)
Prior art keywords
order
features
eigencomponents
component
component features
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
Application number
PCT/JP2003/004550
Other languages
French (fr)
Other versions
WO2003088131A2 (en
Inventor
Yongsheng Gao
Chak Joo Lee
Sheng Mei Shen
Zhongyang Huang
Takanori Senoh
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Panasonic Holdings Corp
Original Assignee
Matsushita Electric Industrial Co Ltd
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 Matsushita Electric Industrial Co Ltd filed Critical Matsushita Electric Industrial Co Ltd
Priority to AU2003226455A priority Critical patent/AU2003226455A1/en
Priority to KR10-2004-7012107A priority patent/KR20040101221A/en
Publication of WO2003088131A2 publication Critical patent/WO2003088131A2/en
Publication of WO2003088131A3 publication Critical patent/WO2003088131A3/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06V40/168—Feature extraction; Face representation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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
    • G06V10/7715—Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Human Computer Interaction (AREA)
  • Computing Systems (AREA)
  • Software Systems (AREA)
  • Medical Informatics (AREA)
  • Evolutionary Computation (AREA)
  • Databases & Information Systems (AREA)
  • Artificial Intelligence (AREA)
  • Image Analysis (AREA)
  • Collating Specific Patterns (AREA)
  • Image Processing (AREA)

Abstract

High-order eigencomponents are proposed to describe detailed regional information of that particular facial component. A formula is given to calculate high-order transform matrix for projection. The high-order component features can be used individually to describe a facial component or combined with first -order component features. Since detailed regional identity information can be revealed with high-order component features, the combination of first-order component features and high-order component features of eyes, eyebrows, nose, mouth and outline with different attention weights, based on the significance of identity information of the corresponding area, has better face description capability compared with the first -order eigenface features or combined first -order and high-order eigenface features.
PCT/JP2003/004550 2002-04-12 2003-04-10 Method and apparatus for face description and recognition using high-order eigencomponents Ceased WO2003088131A2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
AU2003226455A AU2003226455A1 (en) 2002-04-12 2003-04-10 Method and apparatus for face description and recognition using high-order eigencomponents
KR10-2004-7012107A KR20040101221A (en) 2002-04-12 2003-04-10 Method and apparatus for face description and recognition using high-order eigencomponents

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2002110936 2002-04-12
JP2002-110936 2002-04-12

Publications (2)

Publication Number Publication Date
WO2003088131A2 WO2003088131A2 (en) 2003-10-23
WO2003088131A3 true WO2003088131A3 (en) 2004-01-15

Family

ID=29243254

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2003/004550 Ceased WO2003088131A2 (en) 2002-04-12 2003-04-10 Method and apparatus for face description and recognition using high-order eigencomponents

Country Status (4)

Country Link
KR (1) KR20040101221A (en)
CN (1) CN1630875A (en)
AU (1) AU2003226455A1 (en)
WO (1) WO2003088131A2 (en)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2414328A (en) * 2004-05-17 2005-11-23 Mitsubishi Electric Inf Tech Discrimination transforms applied to frequency domain derived feature vectors
US7835549B2 (en) 2005-03-07 2010-11-16 Fujifilm Corporation Learning method of face classification apparatus, face classification method, apparatus and program
US7936906B2 (en) 2007-06-15 2011-05-03 Microsoft Corporation Face recognition using discriminatively trained orthogonal tensor projections
RU2390844C2 (en) * 2007-10-22 2010-05-27 Государственное образовательное учреждение высшего профессионального образования Курский государственный технический университет Method of identifying eyes on images and device for implementing said method

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1217574A2 (en) * 2000-12-19 2002-06-26 Matsushita Electric Industrial Co., Ltd. A method for lighting- and view-angle-invariant face description with first- and second-order eigenfeatures

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1217574A2 (en) * 2000-12-19 2002-06-26 Matsushita Electric Industrial Co., Ltd. A method for lighting- and view-angle-invariant face description with first- and second-order eigenfeatures

Non-Patent Citations (6)

* Cited by examiner, † Cited by third party
Title
KIM M-S ET AL: "Face recognition using the embedded HMM with second-order block-specific observations", PATTERN RECOGNITION, PERGAMON PRESS INC. ELMSFORD, N.Y, US, vol. 36, no. 11, November 2003 (2003-11-01), pages 2723 - 2735, XP004453573, ISSN: 0031-3203 *
KIRP H ET AL: "Face retrieval using 1st- and 2nd-order pca mixture model", PROCEEDINGS 2002 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING. ICIP 2002. ROCHESTER, NY, SEPT. 22 - 25, 2002, INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, NEW YORK, NY: IEEE, US, vol. 2 OF 3, 22 September 2002 (2002-09-22), pages 605 - 608, XP010608044, ISBN: 0-7803-7622-6 *
KOUZANI A Z ET AL: "Multiresolution eigenface-components", TENCON '97. IEEE REGION 10 ANNUAL CONFERENCE. SPEECH AND IMAGE TECHNOLOGIES FOR COMPUTING AND TELECOMMUNICATIONS., PROCEEDINGS OF IEEE BRISBANE, QLD., AUSTRALIA 2-4 DEC. 1997, NEW YORK, NY, USA,IEEE, US, 2 December 1997 (1997-12-02), pages 353 - 356, XP010264172, ISBN: 0-7803-4365-4 *
SHAKUNAGA T ET AL: "Decomposed eigenface for face recognition under various lighting conditions", PROCEEDINGS 2001 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION. CVPR 2001. KAUAI, HAWAII, DEC. 8 - 14, 2001, PROCEEDINGS OF THE IEEE COMPUTER CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, LOS ALAMITOS, CA, IEEE COMP. SOC, US, vol. 1 OF 2, 8 December 2001 (2001-12-08), pages 864 - 871, XP010583836, ISBN: 0-7695-1272-0 *
TURK M A ET AL: "Face recognition using eigenfaces", PROCEEDINGS OF THE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION. LAHAINA, MAUI, HAWAII, JUNE 3 - 6, 1991, LOS ALAMITOS, IEEE. COMP. SOC. PRESS, US, 3 June 1991 (1991-06-03), pages 586 - 591, XP010023267, ISBN: 0-8186-2148-6 *
TURK M ET AL: "EIGENFACES FOR RECOGNITION", JOURNAL OF COGNITIVE NEUROSCIENCE, CAMBRIDGE, MA, US, vol. 3, no. 1, 1991, pages 71 - 86, XP000490270 *

Also Published As

Publication number Publication date
KR20040101221A (en) 2004-12-02
AU2003226455A1 (en) 2003-10-27
AU2003226455A8 (en) 2003-10-27
CN1630875A (en) 2005-06-22
WO2003088131A2 (en) 2003-10-23

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