WO2017128363A1 - Procédé et système de mise en corrélation de données en temps réel sur la base de données volumineuses - Google Patents

Procédé et système de mise en corrélation de données en temps réel sur la base de données volumineuses Download PDF

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Publication number
WO2017128363A1
WO2017128363A1 PCT/CN2016/072930 CN2016072930W WO2017128363A1 WO 2017128363 A1 WO2017128363 A1 WO 2017128363A1 CN 2016072930 W CN2016072930 W CN 2016072930W WO 2017128363 A1 WO2017128363 A1 WO 2017128363A1
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WO
WIPO (PCT)
Prior art keywords
video data
data
real
same person
association
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/CN2016/072930
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English (en)
Chinese (zh)
Inventor
马岩
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.)
Shenzhen Boxinnuoda Economic Relations and Trade Consultants Co Ltd
Original Assignee
Shenzhen Boxinnuoda Economic Relations and Trade Consultants 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 Shenzhen Boxinnuoda Economic Relations and Trade Consultants Co Ltd filed Critical Shenzhen Boxinnuoda Economic Relations and Trade Consultants Co Ltd
Priority to PCT/CN2016/072930 priority Critical patent/WO2017128363A1/fr
Priority to CN201680000297.9A priority patent/CN105830068A/zh
Publication of WO2017128363A1 publication Critical patent/WO2017128363A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G06F16/7837—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using objects detected or recognised in the video content
    • G06F16/784—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using objects detected or recognised in the video content the detected or recognised objects being people

Definitions

  • the present invention relates to the field of communication and Internet of Things, and in particular, to a real-time data association method and system based on big data.
  • a real-time data association method based on big data is provided, which solves the shortcomings of the prior art that the corresponding video data association cannot be provided.
  • a method for real-time data association based on big data comprising the following steps:
  • the video data is subjected to image recognition.
  • the image recognizes that the two video data are the same person the two video data are set as associated data.
  • the method further includes:
  • the three video data are associated.
  • the method further includes:
  • a real-time data association system based on big data comprising:
  • the association unit is configured to perform image recognition on the video data. If the image identifies that the two video data are the same person, the two video data are set as associated data.
  • the association unit is further configured to associate three video data when another video data is identified as being the same person.
  • system further includes:
  • An analysis unit for performing an overall analysis of the associated video data is .
  • the technical solution provided by the specific embodiment of the present invention acquires video data, and performs image recognition on the video data. If the image identifies two video data as the same person, the two video data are set as associated data, so Realize the advantages of video data association.
  • FIG. 1 is a flowchart of a real-time data association method based on big data provided by the present invention
  • FIG. 2 is a structural diagram of a real-time data association system based on big data provided by the present invention.
  • FIG. 1 is a flowchart of a real-time data association method based on big data according to a first preferred embodiment of the present invention.
  • the method is implemented by an intelligent terminal.
  • the method is as shown in FIG. 1 and includes the following steps. :
  • Step S101 Acquire video data.
  • Step S102 Perform image recognition on the video data. If the image identifies that the two video data are the same person, set the two video data as associated data.
  • the technical solution provided by the specific embodiment of the present invention acquires video data, and performs image recognition on the video data. If the image identifies two video data as the same person, the two video data are set as associated data, so Realize the advantages of video data association.
  • the foregoing method may further include:
  • Step S103 If it is recognized that the other video data is also the same person, the three video data are associated.
  • the foregoing method may further include:
  • FIG. 2 is a real-time data association system based on big data according to a second preferred embodiment of the present invention.
  • the system includes:
  • the obtaining unit 201 is configured to acquire video data.
  • the association unit 202 is configured to perform image recognition on the video data. If the image identifies that the two video data are the same person, the two video data are set as associated data.
  • the technical solution provided by the specific embodiment of the present invention acquires video data, and performs image recognition on the video data. If the image identifies two video data as the same person, the two video data are set as associated data, so Realize the advantages of video data association.
  • association unit 202 is further configured to associate three video data when the other video data is also identified as the same person.
  • the above system may further include:
  • the analyzing unit 203 is configured to perform overall analysis on the associated video data.
  • Computer readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one location to another.
  • a storage medium may be any available media that can be accessed by a computer.
  • the computer readable medium may include random access memory (Random) Access Memory, RAM), Read-Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), Compact Disc Read-Only Memory, CD-ROM, or other optical disc storage, magnetic storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also. Any connection may suitably be a computer readable medium.
  • a disk and a disc include a compact disc (CD), a laser disc, a compact disc, a digital versatile disc (DVD), a floppy disk, and a Blu-ray disc, wherein the disc is usually magnetically copied, and the disc is The laser is used to optically replicate the data. Combinations of the above should also be included within the scope of the computer readable media.

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Library & Information Science (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)

Abstract

L'invention concerne un procédé et un système de mise en corrélation de données en temps réel sur la base de données volumineuses. Le procédé comprend les étapes suivantes consistant à : faire l'acquisition de données vidéo (101); effectuer une reconnaissance d'image sur les données vidéo, et si deux données vidéo sont reconnues au moyen de la reconnaissance d'image comme se rapportant à une même personne, régler les deux données vidéo en tant que données corrélées (102). Les solutions techniques fournies par le procédé et le système ont l'avantage de parvenir à une mise en corrélation des données vidéo.
PCT/CN2016/072930 2016-01-30 2016-01-30 Procédé et système de mise en corrélation de données en temps réel sur la base de données volumineuses Ceased WO2017128363A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
PCT/CN2016/072930 WO2017128363A1 (fr) 2016-01-30 2016-01-30 Procédé et système de mise en corrélation de données en temps réel sur la base de données volumineuses
CN201680000297.9A CN105830068A (zh) 2016-01-30 2016-01-30 基于大数据的实时数据关联方法及系统

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2016/072930 WO2017128363A1 (fr) 2016-01-30 2016-01-30 Procédé et système de mise en corrélation de données en temps réel sur la base de données volumineuses

Publications (1)

Publication Number Publication Date
WO2017128363A1 true WO2017128363A1 (fr) 2017-08-03

Family

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Application Number Title Priority Date Filing Date
PCT/CN2016/072930 Ceased WO2017128363A1 (fr) 2016-01-30 2016-01-30 Procédé et système de mise en corrélation de données en temps réel sur la base de données volumineuses

Country Status (2)

Country Link
CN (1) CN105830068A (fr)
WO (1) WO2017128363A1 (fr)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102609686A (zh) * 2012-01-19 2012-07-25 宁波大学 一种行人检测方法
CN102880864A (zh) * 2012-04-28 2013-01-16 王浩 一种从流媒体文件中抓拍人脸的方法
CN103530652A (zh) * 2013-10-23 2014-01-22 北京中视广信科技有限公司 一种基于人脸聚类的视频编目方法、检索方法及其系统

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102609686A (zh) * 2012-01-19 2012-07-25 宁波大学 一种行人检测方法
CN102880864A (zh) * 2012-04-28 2013-01-16 王浩 一种从流媒体文件中抓拍人脸的方法
CN103530652A (zh) * 2013-10-23 2014-01-22 北京中视广信科技有限公司 一种基于人脸聚类的视频编目方法、检索方法及其系统

Also Published As

Publication number Publication date
CN105830068A (zh) 2016-08-03

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