WO2015129332A1 - 商品検索装置、方法及びシステム - Google Patents

商品検索装置、方法及びシステム Download PDF

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Publication number
WO2015129332A1
WO2015129332A1 PCT/JP2015/051243 JP2015051243W WO2015129332A1 WO 2015129332 A1 WO2015129332 A1 WO 2015129332A1 JP 2015051243 W JP2015051243 W JP 2015051243W WO 2015129332 A1 WO2015129332 A1 WO 2015129332A1
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WO
WIPO (PCT)
Prior art keywords
block
sensitivity
product
image
unit
Prior art date
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Ceased
Application number
PCT/JP2015/051243
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English (en)
French (fr)
Japanese (ja)
Inventor
野口　幸典
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.)
Fujifilm Corp
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Fujifilm Corp
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Filing date
Publication date
Application filed by Fujifilm Corp filed Critical Fujifilm Corp
Priority to CN201580008552.XA priority Critical patent/CN105993014A/zh
Priority to EP15754947.8A priority patent/EP3113048A4/en
Publication of WO2015129332A1 publication Critical patent/WO2015129332A1/ja
Priority to US15/205,425 priority patent/US10216818B2/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/258—Data format conversion from or to a database
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/285—Clustering or classification
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06F16/51—Indexing; Data structures therefor; Storage structures
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9032—Query formulation
    • G06F16/90324—Query formulation using system suggestions
    • G06F16/90328—Query formulation using system suggestions using search space presentation or visualization, e.g. category or range presentation and selection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0623—Electronic shopping [e-shopping] by investigating goods or services

Definitions

  • the present invention makes it possible to recommend products with dissimilar images that have different impressions to the general consumer from the specific products, and make consumer purchase decisions compared to the case of displaying product images randomly.
  • the present invention relates to a product search apparatus, method, and system that can be promoted.
  • Patent Document 1 a correlation between a sensory feature amount used to specify an impression felt by a designer from an arbitrary image and a physical feature amount extracted by calculation from an image processing result is obtained in advance by a statistical method.
  • image search at the time of design, a configuration is disclosed in which an image search is performed by obtaining a spatial distance (Euclidean distance) between the sensitivity feature amount of the input image and the sensitivity feature amount of the registered image.
  • the coordinate position of the specific similar designated image designated by the user from the example image menu and the specific The center point of the image search is obtained based on the line segment determined by the coordinate position of the dissimilar designated image, and n registered images having a spatial distance from the center point are searched from the database in order from the nearest registered image.
  • Patent Document 2 a plurality of registered images are stored in advance in a database together with physical feature amounts as a pattern sample, and in the image search at the time of design, the coordinate axes of physical features (for example, line thickness axis, left-right symmetry axis) , And a density axis of the space), when a sensitivity word (for example, “a little sharper”) that defines a shift rule for the reference coordinate position is input by the user, it corresponds to a physical feature amount of a specific image.
  • a shift corresponding to the input sensitivity word from the reference coordinate position (for example, a shift to a coordinate position having a smaller line thickness value) is performed, and an image with a short spatial distance is centered on the shifted reference coordinate position.
  • a configuration for searching from a database is disclosed. As a result, it is possible to accurately search and display an image that is almost the same as the human impression compared to the specific image specified by the user.
  • client device When displaying images of recommended products on a consumer's terminal device (hereinafter referred to as “client device”) via a network, images of multiple recommended products are randomly displayed without considering the consumer's impression of the product image.
  • client device When displayed, there are problems that the images are displayed randomly and the consumer cannot narrow down the product he / she wants to buy, and that the consumer gets tired before finding a favorite product. That is, there is a problem that it is difficult for consumers to make purchase decisions simply by displaying images of recommended products at random.
  • the present invention provides a product search apparatus using a product database that stores a plurality of images corresponding to a plurality of products and physical quantities of product images in association with each other.
  • the physical quantity acquisition unit for acquiring the physical quantity of the image of the specific product, and the physical quantity of the acquired image of the specific product, the physical quantity of the specific product among a plurality of blocks in the sensitivity space in which a plurality of sensitivity words representing human sensitivity are arranged
  • a plurality of blocks in the sensitivity space based on information indicating the specific product sensitivity block obtained by the first conversion unit, which is converted into information indicating the specific product sensitivity block that is a block corresponding to the image;
  • the attention block selection unit that selects a block different from the specific product sensitivity block as the attention block, and information indicating the attention block in the sensitivity space are displayed as the attention block.
  • the block-of-interest selection unit also selects a block arranged between the specific product sensitivity block and the user-specified sensitivity block in the sensitivity space as the block of interest.
  • the product database 102 may store various attribute information about the product such as the product category and the product price in association with the product image 132 in addition to the physical quantity of the product image 132.
  • the pattern feature amount indicates the type (for example, floral pattern) and size of the pattern in the product image.
  • the pattern feature amount measured by image analysis of the product image is stored in the product database 102.
  • the texture feature amount indicates the degree of texture such as gloss of the product image.
  • the texture feature quantity measured by image analysis of the product image is stored in the product database 102.
  • the Kansei space in this specification has the following (Feature 1) to (Feature 3).
  • the Kansei space is a multi-dimensional coordinate space with a plurality of Kansei features as axes.
  • the sensitivity space illustrated in FIG. 4 and FIG. 5 is two-dimensional including the first sensitivity feature amount axis (X axis) and the second sensitivity feature amount axis (Y axis). Good.
  • the sensory feature amount indicates the degree of impression of a person who observes the image.
  • the image scale shown in FIG. 6 is a horizontal axis indicating the degree of WARM (warm) / COOL (cold) corresponding to the axis of the first sensitivity feature amount, and a HARD corresponding to the axis of the second sensitivity feature amount. It consists of a vertical axis indicating the degree of (hard) / SOFT (soft). In addition, 66 sensitivity words are arranged and divided into 16 blocks.
  • the conversion database 106 in FIG. 9 includes a conversion data table T1 indicating the correspondence between the physical quantity range and the information indicating the block.
  • information indicating the block for example, block identification information stored in the sensitivity space database 104 or range information in the sensitivity space of each block can be used.
  • the target block selection unit 120 can also include the specific product sensitivity block denoted by reference number 201 in the target block.
  • the attention block selection unit 120 selects an antonym sensitivity block that is a block including an anti-sensitivity word that is a sensitivity word having a meaning opposite to that of the specific product sensitivity word corresponding to the image of the specific product. , Select as the attention block.
  • the specific product sensitivity word is a word indicating an impression received from an image by a person who observed the image of the specific product.
  • the block corresponding to the sensitivity word designated by the user based on the user designation information by the target block selection unit 120 of the server device 10
  • the user-designated sensitivity block which is a block designated by the user, is selected as the block of interest (step S322).

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Physics & Mathematics (AREA)
  • Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Finance (AREA)
  • Accounting & Taxation (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Development Economics (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • General Business, Economics & Management (AREA)
  • Library & Information Science (AREA)
  • Computational Linguistics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Processing Or Creating Images (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
PCT/JP2015/051243 2014-02-28 2015-01-19 商品検索装置、方法及びシステム Ceased WO2015129332A1 (ja)

Priority Applications (3)

Application Number Priority Date Filing Date Title
CN201580008552.XA CN105993014A (zh) 2014-02-28 2015-01-19 商品搜索装置、方法及系统
EP15754947.8A EP3113048A4 (en) 2014-02-28 2015-01-19 Product retrieval device, method, and system
US15/205,425 US10216818B2 (en) 2014-02-28 2016-07-08 Product search apparatus, method, and system

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2014038523A JP6145416B2 (ja) 2014-02-28 2014-02-28 商品検索装置及び方法、商品検索システム
JP2014-038523 2014-02-28

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US15/205,425 Continuation US10216818B2 (en) 2014-02-28 2016-07-08 Product search apparatus, method, and system

Publications (1)

Publication Number Publication Date
WO2015129332A1 true WO2015129332A1 (ja) 2015-09-03

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US (1) US10216818B2 (enExample)
EP (1) EP3113048A4 (enExample)
JP (1) JP6145416B2 (enExample)
CN (1) CN105993014A (enExample)
WO (1) WO2015129332A1 (enExample)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105760523A (zh) * 2016-02-29 2016-07-13 百度在线网络技术（北京）有限公司 一种信息推送方法和装置
JP2017068616A (ja) * 2015-09-30 2017-04-06 大日本印刷株式会社 画像用言語提示装置、画像用言語提示方法及びプログラム
JP2018067180A (ja) * 2016-10-20 2018-04-26 三菱電機インフォメーションシステムズ株式会社 作業支援装置および作業支援プログラム

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JP6728091B2 (ja) * 2017-03-15 2020-07-22 富士フイルム株式会社 画像合成装置，画像合成方法およびそのプログラム
CN109299715B (zh) 2017-07-24 2021-07-13 图灵通诺（北京）科技有限公司 基于卷积神经网络的图像识别技术的结算方法和装置
JP7138866B2 (ja) * 2019-12-26 2022-09-20 株式会社カルチベイトジャパン 情報表示装置、方法、及びプログラム

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2017068616A (ja) * 2015-09-30 2017-04-06 大日本印刷株式会社 画像用言語提示装置、画像用言語提示方法及びプログラム
CN105760523A (zh) * 2016-02-29 2016-07-13 百度在线网络技术（北京）有限公司 一种信息推送方法和装置
JP2018067180A (ja) * 2016-10-20 2018-04-26 三菱電機インフォメーションシステムズ株式会社 作業支援装置および作業支援プログラム
WO2018073986A1 (ja) * 2016-10-20 2018-04-26 三菱電機株式会社 作業支援装置および作業支援プログラム

Also Published As

Publication number Publication date
CN105993014A (zh) 2016-10-05
JP2015162194A (ja) 2015-09-07
US10216818B2 (en) 2019-02-26
JP6145416B2 (ja) 2017-06-14
EP3113048A4 (en) 2017-03-08
US20160321335A1 (en) 2016-11-03
EP3113048A1 (en) 2017-01-04

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