MX2014011016A - Metodo y dispositivo de agrupamiento. - Google Patents

Metodo y dispositivo de agrupamiento.

Info

Publication number
MX2014011016A
MX2014011016A MX2014011016A MX2014011016A MX2014011016A MX 2014011016 A MX2014011016 A MX 2014011016A MX 2014011016 A MX2014011016 A MX 2014011016A MX 2014011016 A MX2014011016 A MX 2014011016A MX 2014011016 A MX2014011016 A MX 2014011016A
Authority
MX
Mexico
Prior art keywords
objects
weight
distance
classes
similarity
Prior art date
Application number
MX2014011016A
Other languages
English (en)
Other versions
MX346698B (es
Inventor
Bo Zhang
Lin Wang
Tao Zhang
Zhijun Chen
Original Assignee
Xiaomi Inc
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 Xiaomi Inc filed Critical Xiaomi Inc
Publication of MX2014011016A publication Critical patent/MX2014011016A/es
Publication of MX346698B publication Critical patent/MX346698B/es

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • 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
    • G06V10/762—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
    • 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
    • G06V40/172—Classification, e.g. identification

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Databases & Information Systems (AREA)
  • Computing Systems (AREA)
  • Human Computer Interaction (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Image Analysis (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

Las modalidades de la presente divulgación divulgan un método y un dispositivo de agrupamiento. El método de agrupamiento incluye: obtener una distancia ponderada entre clases de acuerdo con un coeficiente de ponderación que corresponde a una distancia inter-objeto, el coeficiente de ponderación se determina de acuerdo con una similitud entre dos objetos, esto es, se pandera la distancia inter-objeto; y después combinar las clases cuyas distancias panderadas cumplen con una condición de combinación, lo cual se termina hasta que el número de las clases después de combinar sea el mismo que el número de las clases antes de combinar, y obtener el resultada de agrupamiento. Debido a que la distancia ponderada se asocia con la similitud de los dos objetos, diferentes distancias entre objetos hacen diferentes contribuciones, mientras mayor es la similitud, más grande es la contribución correspondiente. Por lo tanto, aumenta la precisión del resultado de agrupamiento.
MX2014011016A 2014-03-14 2014-07-24 Metodo y dispositivo de agrupamiento. MX346698B (es)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201410096608.9A CN103927545B (zh) 2014-03-14 2014-03-14 聚类方法及相关装置
PCT/CN2014/082884 WO2015135277A1 (zh) 2014-03-14 2014-07-24 聚类方法及相关装置

Publications (2)

Publication Number Publication Date
MX2014011016A true MX2014011016A (es) 2016-02-19
MX346698B MX346698B (es) 2017-03-28

Family

ID=51145761

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2014011016A MX346698B (es) 2014-03-14 2014-07-24 Metodo y dispositivo de agrupamiento.

Country Status (7)

Country Link
EP (1) EP2919136A1 (es)
JP (1) JP6051336B2 (es)
KR (1) KR101639502B1 (es)
CN (1) CN103927545B (es)
MX (1) MX346698B (es)
RU (1) RU2630373C2 (es)
WO (1) WO2015135277A1 (es)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103927545B (zh) * 2014-03-14 2017-10-17 小米科技有限责任公司 聚类方法及相关装置
CN105488467B (zh) * 2015-11-26 2019-07-23 小米科技有限责任公司 图片分类方法及装置
CN107092618A (zh) * 2016-10-27 2017-08-25 北京小度信息科技有限公司 一种信息处理方法及装置
CN109469919B (zh) * 2018-11-12 2020-07-28 南京工程学院 一种基于权重聚类的电站空预器堵灰监测方法
CN111310834B (zh) * 2020-02-19 2024-05-28 深圳市商汤科技有限公司 数据处理方法及装置、处理器、电子设备、存储介质
CN111415151A (zh) * 2020-03-10 2020-07-14 支付宝(杭州)信息技术有限公司 连锁商户的识别方法、装置、电子设备及存储介质
CN112132111A (zh) * 2020-10-10 2020-12-25 安徽江淮汽车集团股份有限公司 泊车典型场景的提取方法、设备、存储介质及装置

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100312331B1 (ko) * 1998-02-14 2001-12-28 이계철 내용기반영상검색방법및장치
US7664735B2 (en) * 2004-04-30 2010-02-16 Microsoft Corporation Method and system for ranking documents of a search result to improve diversity and information richness
US7809192B2 (en) * 2005-05-09 2010-10-05 Like.Com System and method for recognizing objects from images and identifying relevancy amongst images and information
KR100824698B1 (ko) * 2006-08-25 2008-04-24 인하대학교 산학협력단 이미지 검색기의 적합성 피드백을 위한 공간 위치정보 기반영역 가중치 방법
KR100804678B1 (ko) * 2007-01-04 2008-02-20 삼성전자주식회사 비디오 인물별 신 분류 방법 및 그 시스템
RU2345414C1 (ru) * 2007-08-10 2009-01-27 Общество с ограниченной ответственностью "Рекогмишн" Способ построения системы индексирования для поиска объектов на цифровых изображениях
JP5526955B2 (ja) * 2010-04-09 2014-06-18 ソニー株式会社 顔クラスタリング装置、顔クラスタリング方法、及びプログラム
US9317783B2 (en) * 2010-06-01 2016-04-19 Hewlett-Packard Development Company, L.P. Clustering images
WO2012089902A1 (en) * 2010-12-30 2012-07-05 Nokia Corporation Method, apparatus, and computer program product for image clustering
US20120294540A1 (en) * 2011-05-17 2012-11-22 Microsoft Corporation Rank order-based image clustering
CN102881032B (zh) * 2012-09-14 2015-09-09 北京理工大学 一种基于改进算法的图片拼接方法
CN103136355B (zh) * 2013-03-05 2016-01-06 电子科技大学 一种基于自动阈值鱼群算法的文本聚类方法
CN103544255B (zh) * 2013-10-15 2017-01-11 常州大学 基于文本语义相关的网络舆情信息分析方法
CN103927545B (zh) * 2014-03-14 2017-10-17 小米科技有限责任公司 聚类方法及相关装置

Also Published As

Publication number Publication date
CN103927545B (zh) 2017-10-17
JP2016517110A (ja) 2016-06-09
WO2015135277A1 (zh) 2015-09-17
EP2919136A1 (en) 2015-09-16
KR20150117201A (ko) 2015-10-19
RU2015129671A (ru) 2017-04-27
MX346698B (es) 2017-03-28
KR101639502B1 (ko) 2016-07-22
RU2630373C2 (ru) 2017-09-07
CN103927545A (zh) 2014-07-16
JP6051336B2 (ja) 2016-12-27

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