WO2006103241A3 - Système et procédé de localisation de points d'intérêt dans une image d'objet mettant en œuvre un réseau de neurones - Google Patents

Système et procédé de localisation de points d'intérêt dans une image d'objet mettant en œuvre un réseau de neurones Download PDF

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Publication number
WO2006103241A3
WO2006103241A3 PCT/EP2006/061110 EP2006061110W WO2006103241A3 WO 2006103241 A3 WO2006103241 A3 WO 2006103241A3 EP 2006061110 W EP2006061110 W EP 2006061110W WO 2006103241 A3 WO2006103241 A3 WO 2006103241A3
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WO
WIPO (PCT)
Prior art keywords
object image
interest
neural network
neurons
intermediate layer
Prior art date
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PCT/EP2006/061110
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English (en)
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WO2006103241A2 (fr
Inventor
Christophe Garcia
Stefan Duffner
Original Assignee
France Telecom
Christophe Garcia
Stefan Duffner
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 France Telecom, Christophe Garcia, Stefan Duffner filed Critical France Telecom
Priority to EP06725370A priority Critical patent/EP1866834A2/fr
Priority to US11/910,159 priority patent/US20080201282A1/en
Priority to JP2008503506A priority patent/JP2008536211A/ja
Publication of WO2006103241A2 publication Critical patent/WO2006103241A2/fr
Publication of WO2006103241A3 publication Critical patent/WO2006103241A3/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/048—Activation functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • 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
    • G06V40/168—Feature extraction; Face representation
    • G06V40/171—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships

Abstract

L'invention concerne un système de localisation d'au moins deux points d'intérêt dans une image d'objet. Selon l'invention, un tel système met en œuvre un réseau de neurones artificiels et présente une architecture en couches comprenant: une couche d'entrée (E) recevant ladite image d'objet; au moins une couche intermédiaire (N4), appelée première couche intermédiaire, comprenant une pluralité de neurones (N41) permettant de générer au moins deux cartes de saillance (R5m) associées chacune à un point d'intérêt distinct prédéfini de ladite image d'objet; au moins une couche de sortie (R5) comprenant lesdites cartes de saillance (R5m) lesdites cartes de saillance comprenant une pluralité de neurones connectés chacun à tous les neurones de ladite première couche intermédiaire, lesdits points d'intérêt étant localisés, dans ladite image d'objet, par la position (171, 172, 173, 174) d'un maximum global unique sur chacune desdites cartes de saillance.
PCT/EP2006/061110 2005-03-31 2006-03-28 Système et procédé de localisation de points d'intérêt dans une image d'objet mettant en œuvre un réseau de neurones WO2006103241A2 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
EP06725370A EP1866834A2 (fr) 2005-03-31 2006-03-28 Système et procédé de localisation de points d'intérêt dans une image d'objet mettant en uvre un réseau de neurones
US11/910,159 US20080201282A1 (en) 2005-03-31 2006-03-28 System and Method for Locating Points of Interest in an Object Image Implementing a Neural Network
JP2008503506A JP2008536211A (ja) 2005-03-31 2006-03-28 ニューラルネットワークを実現するオブジェクトイメージにおいて興味のあるポイントを位置決めするシステム及び方法

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR0503177A FR2884008A1 (fr) 2005-03-31 2005-03-31 Systeme et procede de localisation de points d'interet dans une image d'objet mettant en oeuvre un reseau de neurones
FR0503177 2005-03-31

Publications (2)

Publication Number Publication Date
WO2006103241A2 WO2006103241A2 (fr) 2006-10-05
WO2006103241A3 true WO2006103241A3 (fr) 2007-01-11

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2006/061110 WO2006103241A2 (fr) 2005-03-31 2006-03-28 Système et procédé de localisation de points d'intérêt dans une image d'objet mettant en œuvre un réseau de neurones

Country Status (6)

Country Link
US (1) US20080201282A1 (fr)
EP (1) EP1866834A2 (fr)
JP (1) JP2008536211A (fr)
CN (1) CN101171598A (fr)
FR (1) FR2884008A1 (fr)
WO (1) WO2006103241A2 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105260776A (zh) * 2015-09-10 2016-01-20 华为技术有限公司 神经网络处理器和卷积神经网络处理器

Families Citing this family (73)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009155415A2 (fr) * 2008-06-20 2009-12-23 Research Triangle Institute Système d'entraînement et de réadaptation, et procédé et programme informatique associés
US8374436B2 (en) * 2008-06-30 2013-02-12 Thomson Licensing Method for detecting layout areas in a video image and method for generating an image of reduced size using the detection method
US8229209B2 (en) * 2008-12-26 2012-07-24 Five Apes, Inc. Neural network based pattern recognizer
US8160354B2 (en) * 2008-12-26 2012-04-17 Five Apes, Inc. Multi-stage image pattern recognizer
US8290250B2 (en) 2008-12-26 2012-10-16 Five Apes, Inc. Method and apparatus for creating a pattern recognizer
KR101558553B1 (ko) * 2009-02-18 2015-10-08 삼성전자 주식회사 아바타 얼굴 표정 제어장치
CN101639937B (zh) * 2009-09-03 2011-12-14 复旦大学 一种基于人工神经网络的超分辨率方法
US9405975B2 (en) 2010-03-26 2016-08-02 Brain Corporation Apparatus and methods for pulse-code invariant object recognition
US9906838B2 (en) 2010-07-12 2018-02-27 Time Warner Cable Enterprises Llc Apparatus and methods for content delivery and message exchange across multiple content delivery networks
US10424342B2 (en) 2010-07-28 2019-09-24 International Business Machines Corporation Facilitating people search in video surveillance
US9134399B2 (en) 2010-07-28 2015-09-15 International Business Machines Corporation Attribute-based person tracking across multiple cameras
US8515127B2 (en) 2010-07-28 2013-08-20 International Business Machines Corporation Multispectral detection of personal attributes for video surveillance
US8532390B2 (en) 2010-07-28 2013-09-10 International Business Machines Corporation Semantic parsing of objects in video
CN102567397B (zh) * 2010-12-30 2014-08-06 高德软件有限公司 兴趣点、连锁店分店兴趣点关联标记的方法与装置
US9224090B2 (en) 2012-05-07 2015-12-29 Brain Corporation Sensory input processing apparatus in a spiking neural network
US9412041B1 (en) 2012-06-29 2016-08-09 Brain Corporation Retinal apparatus and methods
US9186793B1 (en) 2012-08-31 2015-11-17 Brain Corporation Apparatus and methods for controlling attention of a robot
US9311594B1 (en) 2012-09-20 2016-04-12 Brain Corporation Spiking neuron network apparatus and methods for encoding of sensory data
US9218563B2 (en) * 2012-10-25 2015-12-22 Brain Corporation Spiking neuron sensory processing apparatus and methods for saliency detection
US9111226B2 (en) 2012-10-25 2015-08-18 Brain Corporation Modulated plasticity apparatus and methods for spiking neuron network
US9183493B2 (en) 2012-10-25 2015-11-10 Brain Corporation Adaptive plasticity apparatus and methods for spiking neuron network
US9275326B2 (en) 2012-11-30 2016-03-01 Brain Corporation Rate stabilization through plasticity in spiking neuron network
US9239985B2 (en) 2013-06-19 2016-01-19 Brain Corporation Apparatus and methods for processing inputs in an artificial neuron network
US9436909B2 (en) 2013-06-19 2016-09-06 Brain Corporation Increased dynamic range artificial neuron network apparatus and methods
US9552546B1 (en) 2013-07-30 2017-01-24 Brain Corporation Apparatus and methods for efficacy balancing in a spiking neuron network
CN103489107B (zh) * 2013-08-16 2015-11-25 北京京东尚科信息技术有限公司 一种制作虚拟试衣模特图像的方法和装置
US9984326B1 (en) * 2015-04-06 2018-05-29 Hrl Laboratories, Llc Spiking neural network simulator for image and video processing
US10198689B2 (en) 2014-01-30 2019-02-05 Hrl Laboratories, Llc Method for object detection in digital image and video using spiking neural networks
US9533413B2 (en) 2014-03-13 2017-01-03 Brain Corporation Trainable modular robotic apparatus and methods
US9987743B2 (en) 2014-03-13 2018-06-05 Brain Corporation Trainable modular robotic apparatus and methods
US9195903B2 (en) 2014-04-29 2015-11-24 International Business Machines Corporation Extracting salient features from video using a neurosynaptic system
CN103955718A (zh) * 2014-05-15 2014-07-30 厦门美图之家科技有限公司 一种图像主体对象的识别方法
KR101563569B1 (ko) * 2014-05-28 2015-10-28 한국과학기술원 학습형 다이내믹 시각 이미지 패턴 인식 시스템 및 방법
EP3149653A4 (fr) * 2014-05-29 2017-06-14 Beijing Kuangshi Technology Co., Ltd. Localisation de point de repère facial à l'aide de réseaux neuronaux en cascade grossiers à fins
US9373058B2 (en) 2014-05-29 2016-06-21 International Business Machines Corporation Scene understanding using a neurosynaptic system
US10115054B2 (en) 2014-07-02 2018-10-30 International Business Machines Corporation Classifying features using a neurosynaptic system
US9798972B2 (en) 2014-07-02 2017-10-24 International Business Machines Corporation Feature extraction using a neurosynaptic system for object classification
US9881349B1 (en) 2014-10-24 2018-01-30 Gopro, Inc. Apparatus and methods for computerized object identification
KR102288280B1 (ko) 2014-11-05 2021-08-10 삼성전자주식회사 영상 학습 모델을 이용한 영상 생성 방법 및 장치
US10650508B2 (en) 2014-12-03 2020-05-12 Kla-Tencor Corporation Automatic defect classification without sampling and feature selection
CN106033594B (zh) * 2015-03-11 2018-11-13 日本电气株式会社 基于卷积神经网络所获得特征的空间信息恢复方法及装置
CN108027896A (zh) * 2015-03-18 2018-05-11 赫尔实验室有限公司 用于解码具有连续突触可塑性的脉冲储层的系统和方法
US9934437B1 (en) 2015-04-06 2018-04-03 Hrl Laboratories, Llc System and method for real-time collision detection
US9933264B2 (en) 2015-04-06 2018-04-03 Hrl Laboratories, Llc System and method for achieving fast and reliable time-to-contact estimation using vision and range sensor data for autonomous navigation
US9840003B2 (en) 2015-06-24 2017-12-12 Brain Corporation Apparatus and methods for safe navigation of robotic devices
CN107851195B (zh) * 2015-07-29 2022-02-11 诺基亚技术有限公司 利用神经网络进行目标检测
JP2017059207A (ja) * 2015-09-18 2017-03-23 パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカＰａｎａｓｏｎｉｃ Ｉｎｔｅｌｌｅｃｔｕａｌ Ｐｒｏｐｅｒｔｙ Ｃｏｒｐｏｒａｔｉｏｎ ｏｆ Ａｍｅｒｉｃａ 画像認識方法
CN105205504B (zh) * 2015-10-04 2018-09-18 北京航空航天大学 一种基于数据驱动的图像关注区域质量评价指标学习方法
US20170124409A1 (en) * 2015-11-04 2017-05-04 Nec Laboratories America, Inc. Cascaded neural network with scale dependent pooling for object detection
KR102554149B1 (ko) * 2015-11-16 2023-07-12 삼성전자주식회사 오브젝트 인식 방법 및 장치, 인식 모델 학습 방법 및 장치
US10860887B2 (en) * 2015-11-16 2020-12-08 Samsung Electronics Co., Ltd. Method and apparatus for recognizing object, and method and apparatus for training recognition model
US10055652B2 (en) * 2016-03-21 2018-08-21 Ford Global Technologies, Llc Pedestrian detection and motion prediction with rear-facing camera
CN107315571B (zh) * 2016-04-27 2020-07-31 中科寒武纪科技股份有限公司 一种用于执行全连接层神经网络正向运算的装置和方法
WO2018052587A1 (fr) * 2016-09-14 2018-03-22 Konica Minolta Laboratory U.S.A., Inc. Procédé et système de segmentation d'image de cellule à l'aide de réseaux neuronaux convolutifs à étages multiples
KR101804840B1 (ko) 2016-09-29 2017-12-05 연세대학교 산학협력단 컨벌루션 신경망 기반의 표면 영상 처리 방법 및 장치
KR101944536B1 (ko) * 2016-12-11 2019-02-01 주식회사 딥바이오 뉴럴 네트워크를 이용한 질병의 진단 시스템 및 그 방법
CN106778751B (zh) * 2017-02-20 2020-08-21 迈吉客科技（北京）有限公司 一种非面部roi识别方法及装置
JP6214073B2 (ja) * 2017-03-16 2017-10-18 ヤフー株式会社 生成装置、生成方法、及び生成プログラム
CN108259496B (zh) 2018-01-19 2021-06-04 北京市商汤科技开发有限公司 特效程序文件包的生成及特效生成方法与装置、电子设备
CN112860168B (zh) 2018-02-08 2022-08-02 北京市商汤科技开发有限公司 特效程序文件包的生成及特效生成方法与装置、电子设备
JP6757349B2 (ja) 2018-03-12 2020-09-16 株式会社東芝 固定小数点を用いて認識処理を行う多層の畳み込みニューラルネットワーク回路を実現する演算処理装置
US20190286988A1 (en) * 2018-03-15 2019-09-19 Ants Technology (Hk) Limited Feature-based selective control of a neural network
JP6996455B2 (ja) * 2018-08-31 2022-01-17 オムロン株式会社 検出器生成装置、モニタリング装置、検出器生成方法及び検出器生成プログラム
JP7035912B2 (ja) * 2018-08-31 2022-03-15 オムロン株式会社 検出器生成装置、モニタリング装置、検出器生成方法及び検出器生成プログラム
US11430084B2 (en) 2018-09-05 2022-08-30 Toyota Research Institute, Inc. Systems and methods for saliency-based sampling layer for neural networks
CN109491704A (zh) * 2018-11-08 2019-03-19 北京字节跳动网络技术有限公司 用于处理信息的方法和装置
CN109744996B (zh) * 2019-01-11 2021-06-15 中南大学 Oct图像的bmo位置定位方法
US11080884B2 (en) * 2019-05-15 2021-08-03 Matterport, Inc. Point tracking using a trained network
CN112825115A (zh) * 2019-11-20 2021-05-21 北京眼神智能科技有限公司 基于单目图像的眼镜检测方法、装置、存储介质及设备
US11687778B2 (en) 2020-01-06 2023-06-27 The Research Foundation For The State University Of New York Fakecatcher: detection of synthetic portrait videos using biological signals
CN116134535A (zh) * 2020-07-23 2023-05-16 第一百欧有限公司 利用半监督学习对疾病发病区域进行注解的方法及执行其的诊断系统
US11532147B2 (en) * 2020-09-25 2022-12-20 Microsoft Technology Licensing, Llc Diagnostic tool for deep learning similarity models
KR20240056112A (ko) * 2022-10-21 2024-04-30 삼성전자주식회사 이미지에서 관심 영역을 식별하기 위한 전자 장치 및 그 제어 방법

Non-Patent Citations (14)

* Cited by examiner, † Cited by third party
Title
ANDREW T. DUCHOWSKI: "Eye Tracking", 2003, SPRINGER, XP002401156 *
GARCIA C ET AL: "CONVOLUTIONAL FACE FINDER: A NEURAL ARCHITECTURE FOR FAST AND ROBUST FACE DETECTION", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, IEEE SERVICE CENTER, LOS ALAMITOS, CA, US, vol. 26, no. 11, November 2004 (2004-11-01), pages 1408 - 1423, XP008039814, ISSN: 0162-8828 *
ITTI L ET AL: "A MODEL OF SALIENCY-BASED VISUAL ATTENTION FOR RAPID SCENE ANALYSIS", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, IEEE SERVICE CENTER, LOS ALAMITOS, CA, US, vol. 20, no. 11, November 1998 (1998-11-01), pages 1254 - 1259, XP001203933, ISSN: 0162-8828 *
ITTI L ET AL: "FEATURE COMBINATION STRATEGIES FOR SALIENCY-BASED VISUAL ATTENTION SYSTEMS", JOURNAL OF ELECTRONIC IMAGING, SPIE / IS & T, US, vol. 10, no. 1, January 2001 (2001-01-01), pages 161 - 169, XP001203934, ISSN: 1017-9909 *
JUELL P ET AL: "A hierarchical neural network for human face detection", PATTERN RECOGNITION, ELSEVIER, KIDLINGTON, GB, vol. 29, no. 5, May 1996 (1996-05-01), pages 781 - 787, XP004021638, ISSN: 0031-3203 *
LECUN Y ET AL: "BACKPROPAGATION APPLIED TO HANDWRITTEN ZIP CODE RECOGNITION", NEURAL COMPUTATION, MASSACHUSETTS INSTITUTE OF TECHNOLOGY, US, vol. 1, 1989, pages 541 - 551, XP000789854, ISSN: 0899-7667 *
LECUN Y ET AL: "CONVOLUTIONAL NETWORKS FOR IMAGES, SPEECH, AND TIME SERIES", HANDBOOK OF BRAIN THEORY AND NEURAL NETWORK, XX, XX, 1995, pages 255 - 258, XP008060061 *
LECUN Y ET AL: "GRADIENT-BASED LEARNING APPLIED TO DOCUMENT RECOGNITION", PROCEEDINGS OF THE IEEE, IEEE. NEW YORK, US, vol. 86, no. 11, November 1998 (1998-11-01), pages 2278 - 2323, XP000875095, ISSN: 0018-9219 *
MATSUGU M ET AL: "Convolutional spiking neural network model for robust face detection", NEURAL INFORMATION PROCESSING, 2002. ICONIP '02. PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NOV. 18-22, 2002, PISCATAWAY, NJ, USA,IEEE, vol. 2, 18 November 2002 (2002-11-18), pages 660 - 664, XP010638800, ISBN: 981-04-7524-1 *
MATSUGU M ET AL: "Subject independent facial expression recognition with robust face detection using a convolutional neural network", NEURAL NETWORKS, ELSEVIER SCIENCE PUBLISHERS, BARKING, GB, vol. 16, no. 5-6, June 2003 (2003-06-01), pages 555 - 559, XP004433973, ISSN: 0893-6080 *
ROWLEY H A ET AL: "HUMAN FACE DETECTION IN VISUAL SCENES", TECHNICAL REPORT CMU-CS-95-158R, November 1995 (1995-11-01), pages COMPLETE, XP001091562 *
ROWLEY H A ET AL: "NEURAL NETWORK-BASED FACE DETECTION", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, IEEE SERVICE CENTER, LOS ALAMITOS, CA, US, vol. 20, no. 1, January 1998 (1998-01-01), pages 23 - 38, XP000753322, ISSN: 0162-8828 *
S. DUFFNER ET C. GARCIA: "A connexionist approach for robust and precise facial feature detection in complex scenes", PORC. INT SYMP ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS ISPA 2005, 15 September 2005 (2005-09-15), Paris, pages 316 - 321, XP002401163 *
VAILLANT R ET AL: "An original approach for the localization of objects in images", ARTIFICIAL NEURAL NETWORKS, 1993., THIRD INTERNATIONAL CONFERENCE ON BRIGHTON, UK, LONDON, UK,IEE, UK, 1993, pages 26 - 30, XP006513936, ISBN: 0-85296-573-7 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105260776A (zh) * 2015-09-10 2016-01-20 华为技术有限公司 神经网络处理器和卷积神经网络处理器

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JP2008536211A (ja) 2008-09-04
FR2884008A1 (fr) 2006-10-06
EP1866834A2 (fr) 2007-12-19
WO2006103241A2 (fr) 2006-10-05
CN101171598A (zh) 2008-04-30
US20080201282A1 (en) 2008-08-21

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