EP2055101A2 - Distribution et adaptation automatisees de contenu multimedia - Google Patents

Distribution et adaptation automatisees de contenu multimedia

Info

Publication number
EP2055101A2
EP2055101A2 EP07755234A EP07755234A EP2055101A2 EP 2055101 A2 EP2055101 A2 EP 2055101A2 EP 07755234 A EP07755234 A EP 07755234A EP 07755234 A EP07755234 A EP 07755234A EP 2055101 A2 EP2055101 A2 EP 2055101A2
Authority
EP
European Patent Office
Prior art keywords
audience
display
information
potential
service
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.)
Withdrawn
Application number
EP07755234A
Other languages
German (de)
English (en)
Inventor
Gael Chardon
Olivier Duizabo
Gilles Mazars
Paolo Prandoni
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.)
Quividi
Businger Peter
Original Assignee
Quividi
Businger Peter
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 Quividi, Businger Peter filed Critical Quividi
Publication of EP2055101A2 publication Critical patent/EP2055101A2/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising

Definitions

  • the invention concerns delivery of media content to an audience and, more particularly, of content comprising advertisements.
  • audience targeting In advertising, irrespective of the delivery medium, there is a primary concern with audience targeting. Subject to a constraint on deployment costs, the goal is to maximize the impact of a campaign by addressing each message to a subset of a potential audience, with the subset chosen for maximized relevancy of the message to members of the subset.
  • Context-based The choice of the audience subset can be implicit in context targeted by a medium. For example, magazines directed to a female audience will mostly carry advertisement directed to women.
  • Usage-based The audience subset may be determined by usage patterns. TV advertisement placed in early-afternoon time slots, for example, will be mostly directed to children.
  • User-based For greater selectivity and efficacy, a campaign can be targeted to individuals or groups of individuals based on their known preferences and/or purchasing patterns. Examples are direct-mail and telephone marketing campaigns. While user-based subset selections are most powerful, often they are costly to deploy as they require detailed market-based analysis. But one medium where deployment costs can be kept low is the internet, as individual users can be characterized on the basis of their usage patterns, on a real-time basis even.
  • a particularly fortuitous situation presents itself to the advertising services that most search engines offer: on entering queries, users implicitly declare an interest in a subject, so that advertising messages can be displayed on their screens according to a criterion of relevance to a query.
  • a fast-growing sector in the advertising industry is that of digital signage, including audiovisual out-of-home advertising installations utilizing digital display devices such as flat-screen monitors.
  • the following represent examples of ways for obtaining user data for such display installations: Indirect Method.
  • the visibility of an installation is estimated from exogenous parameters such as its location with respect to people flows or location attendance.
  • Polling Method A random sample of a potential audience — in a shopping mall, for example — is explicitly asked about the visibility of an installation by pollsters.
  • a chosen sample of a potential audience e.g. of households with a TV — is asked to keep a record of the visibility of an installation. This might include written diary entries, or might involve an automated method relying on a device which a user activates to identify him/herself.
  • OTS Operat Transfer to See
  • Impact for a potential audience.
  • no reactions, opinions and other higher-level information about the effect of the installation on an audience can be inferred.
  • Polling and rating methods while potentially more powerful than the indirect method, still suffer from two major drawbacks.
  • attributes of subjects in front of an installation can be ascertained in an automated fashion.
  • the attributes can include gender, age, clothing style and hairstyle, for example, which can be combined with customary context and usage-pattern data in selecting messages suitable for display at the installation.
  • Customary data include geographical location and time. The combined data can be supplied to a number of potential content providers with an invitation for them to bid in an auction of display time.
  • Fig. 1 is a block schematic of a content adaptation system in accordance with an exemplary embodiment of the invention.
  • Fig. 2 is a block schematic of a functional module or subsystem of the content adaptation system of Fig. 1.
  • Fig. 3 is a block schematic of a functional module which can be coupled to the content adaptation system of Fig. I 5 in accordance with a further exemplary embodiment of the invention.
  • Fig. 4 is a block schematic of a functional module or subsystem of the content adaptation system of Fig. 1, alternative to and more elaborate than the functional module of Fig. 2.
  • Fig. 1 shows a content adaptation system 10 (also labeled as SBlOO in the figure) including a video camera 11 (CM-O) which can be understood as placed in the vicinity of a signage installation or screen for capturing the scene in front of the screen.
  • Signals from the video camera 11 are input to a subsystem 12 (SB-300) for processing into a series of high-level descriptors for any audience in front of the screen. Examples of descriptors are the number of people, the number of people actually watching the screen, audience gender breakdown, audience age breakdown, viewers' features, e.g. glasses, beard and hairstyle, and group dynamics such as family, crowd or single individuals.
  • the generated descriptors are fed to a module
  • Geographical identifiers can play a qualifier role similar to that of parameters employed in usage-based targeting methods, as there typically is a relationship between venue and typical audience base. Examples of geographical identifiers are designations of state, city and street, type of venue such as grocery store, apparel store or train station, and location within venue, e.g. produce aisle, ticket counter and the like.
  • Module 13 translates the audience data from subsystem 12, the time stamp, and the geographical index into a query for database 16 (DB-20), namely a repository of pre-tagged display material such as video files suitable for reproduction on display device 17 (DD-50).
  • the tags associated with the display material are metadata which describe the suitability of the content for a given audience, time and location.
  • the metadata are in standardized format and are exploitable via the standard database queries generated by module 13. Examples of queries - here translated into human language — are: "retrieve content suitable for a female audience at lunchtime in a grocery store”, "retrieve content suitable for a group of three young males on a Friday afternoon in a movie theater", or "retrieve content suitable for a family group”.
  • Each item in database 16 is also marked by a unique owner's ID.
  • the output data from module 13 can be differently routed by switch 18 (SW-30). If switch 18 is in position SW-A, the system 10 can be said to function in local mode in which a query from module 13 is routed directly to the local database 16, for the results which best match the query to be sent to the display device 17. If the switch 18 is in position SW-B, the system 10 can be said to function in centralized mode in which a query from module 13 is sent to a subsystem 19 (SB-200) which modifies or augments the query before returning it for submission to the local database 16. Such modification most notably includes the addition of a specific owner's ID to the query parameters.
  • SB-200 subsystem 19
  • Fig. 2 shows a subsystem 20 (also labeled as SB-300 in the figure) for analyzing the images captured by the camera 11 in order to extract audience data including high-level descriptors for the installation's audience.
  • the camera signal is input to a module 21 (PD-10) for detecting the presence of people in front of the installation.
  • PD-10 a module 21 for detecting the presence of people in front of the installation.
  • Such detection triggers the module 22 (PT-11) for tracking the ensemble of detections and for establishing spatio-temporal relations for the detections.
  • a module 23 (P A-20) analyzes the detections to extract high-level descriptors such as individual height, body size, type of clothes, colors and the like, and a face detection module 24 (FD-21) extracts additional information from the detections such as gender, age, hair style and the like.
  • a final module 25 (FE-22) extracts from the detections a directionality descriptor for the individual's gaze, which can be used to determine whether a person in the audience is actually looking at the installation.
  • Module 25 can optionally connect to a local database 26 (DDB-51) which contains previously stored descriptors for known faces in order to perform face recognition and to output a named descriptor of the person.
  • DDB-51 local database 26
  • the aggregate of all the information extracted by the modules is the output of subsystem 20.
  • Fig. 3 shows a subsystem 30 (also labeled as SB-200 in the figure) which is active in centralized mode.
  • the subsystem 30 includes a module 31 (CO- 80) which is connected to a plurality of distinct, geographically distributed subsystems 32 (SB-100-1, SB- 100-2, . . ., SB-IOO-N).
  • Database queries constructed locally within each of the subsystems 32 are forwarded to module 31 via communications links which can be standard TCP-IP links (Transmission Control Protocol — Internet Protocol).
  • a database 33 (DB-81) mirrors the contents of the subsystems 32, so that queries issued from the subsystems 32 to the database 33 yield consistent results.
  • the module 31 is connected to a plurality of bidding modules 34 (UI-82-1, . .
  • the bidding modules 82 are accessible to the owners of display material stored on database 33 and on the local databases 16 at each subsystem 10. Each module 34 is identified by the same owner ID as used in the database.
  • module 32 Upon receipt of a query from one of the subsystems 10, module 32 retrieves the best-matched results from database 33 and notifies the bidding modules 34 which correspond to the owners' IDs associated with the results, thereby to trigger an auction of display time. On their examination of the results, the notified owners can respond by bidding for display time, and the highest bidder can be awarded control of the display for a period of time. Conveniently for awarding, module 31 complements the query with the highest bidder's ID and returns the query to the local module 10. Only the display material marked with that bidder's ID will be forwarded to the display device(s) 17.
  • Fig. 4 shows a subsystem 40 (also labeled as SB-100 in the figure) alternative to the system of Fig. 1 and 2, in real time providing for enhanced audience data gathering.
  • the subsystem 40 includes a camera 41 (CM-O) for capturing the scene in front of the installation for which audience measurement is sought.
  • the camera 41 is connected to a module 42 (PD-10) for detecting the presence of people in front of the installation and for triggering the operation of subsequent systems modules.
  • module 43 PT-11
  • Module 44 (MA- 12) analyzes the motion patterns of individuals to arrive at higher-level information such as the presence of groups of people, their average spacing, their mutual interactions and the like.
  • the resulting data are time- stamped and recorded onto a local database 45 (DB-50).
  • Data of each person detected by module 43 is input also to one of a plurality of subsystems 46 (SB-101).
  • the gateway to subsystem 46 is an analysis module 47 (PA-20) which, for each person in the audience, extracts biometric features such as height, body size, gait and the like. These data are stored in the database 45.
  • the module 47 further specializes into a face detection module 48 (FD- 21) which detects the face of the person and extracts a set of compact features for analysis by a module 49 (FE-22). There result a series of high-level descriptors for the person, e.g. the person's gender, age, hairstyle and the like. These data are stored on local database 45.
  • Module 49 optionally can connect to a local database 50 (DB- 51) which includes previously stored descriptors for known faces in order to facilitate face recognition and to ouput a named descriptor for the person.
  • Module 49 also outputs a directionality descriptor for the person's gaze, which is used by decision module 51 (GD-23) to determine whether a person in the audience is actively looking at the installation. If so, a module 52 (AS-24) is triggered to start a log-taking activity for the attention span relative to the tracked audience member, optionally links the attention span to the content displayed by the installation at the time which is available from an external source 53 (CI-40). These data are stored on the local database 45 and updated for the entire duration of the attention span.
  • DB- 51 local database 50
  • CI-40 external source 53
  • a complete system SB-200 of Fig. 2 can include a plurality of interconnected subsystems 40, with the camera 41 of each subsystem 40 located in the vicinity of a visual installation for which monitoring is sought. Interconnection between subsystems 40 can be effected by any suitable communication means, e.g. a TCP/IP link.
  • the local data of each subsystem 40 is accessible by a main module 31 which gathers the audience measurement data from the individual subsystems 40 and stores it locally on a database 33.
  • the data can be organized and arranged according to specific user requirement communicated to the module 31 via a control interface 34. Examples of queries include the global effective audience for the aggregate of installations, the global OTS for the aggregate installations, the effective audience for a single installation, the audience breakdown by location, the audience breakdown by gender, the audience breakdown by age, the average attention span of the audience and the like.
  • the bidding modules include a straightforward two-way data exchange interface which can be implemented as a web page with HTTP forms (Hypertext Transfer Protocol).

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Development Economics (AREA)
  • Strategic Management (AREA)
  • Finance (AREA)
  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

Selon la présente invention, dans le domaine de la publicité, indépendamment du support de distribution, il est possible d'aborder le problème du ciblage du public par des techniques basées sur le contexte, basées sur l'utilisation et basées sur l'utilisateur. Dans un secteur à croissance rapide de l'industrie de la publicité, à savoir la signalisation numérique, les données utilisateur destinées aux installations d'affichage sont obtenues par des procédés désignés comme indirects, d'appel ou d'évaluation. Au-delà du ciblage basé sur le contexte et basé sur l'utilisation, pour la facilitation de l'adaptation de contenu basé sur le public ou le ciblage, il est possible de déterminer de façon automatisée les attributs physiques de sujets devant une installation. Les attributs peuvent être combinés avec le contexte habituel et les données de modèle d'utilisation en sélectionnant des messages appropriés pour l'affichage sur l'installation. Les données combinées peuvent être fournies à un nombre de fournisseurs de contenu potentiels avec une invitation à faire une offre lors d'enchères portant sur du temps d'affichage.
EP07755234A 2006-04-10 2007-04-10 Distribution et adaptation automatisees de contenu multimedia Withdrawn EP2055101A2 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US79076906P 2006-04-10 2006-04-10
US79077006P 2006-04-10 2006-04-10
PCT/US2007/008898 WO2007120686A2 (fr) 2006-04-10 2007-04-10 Distribution et adaptation automatisees de contenu multimedia

Publications (1)

Publication Number Publication Date
EP2055101A2 true EP2055101A2 (fr) 2009-05-06

Family

ID=38610142

Family Applications (1)

Application Number Title Priority Date Filing Date
EP07755234A Withdrawn EP2055101A2 (fr) 2006-04-10 2007-04-10 Distribution et adaptation automatisees de contenu multimedia

Country Status (2)

Country Link
EP (1) EP2055101A2 (fr)
WO (1) WO2007120686A2 (fr)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007128057A1 (fr) 2006-05-04 2007-11-15 National Ict Australia Limited Systeme médiatique electronique
US9563970B2 (en) * 2010-01-15 2017-02-07 Digimarc Corporation Methods and arrangements relating to signal rich art
CA2956015A1 (fr) * 2014-08-04 2016-02-11 Quividi Processus de surveillance du public dans une region ciblee
US9900278B2 (en) 2015-06-09 2018-02-20 International Business Machines Corporation Eliciting positive responses to a social media posting
US10497014B2 (en) 2016-04-22 2019-12-03 Inreality Limited Retail store digital shelf for recommending products utilizing facial recognition in a peer to peer network
US20180101872A1 (en) * 2016-10-11 2018-04-12 Broadsign International Llc Method and computing device for optimizing placement of digital signage content based on audience segments
US11263665B2 (en) 2019-12-19 2022-03-01 Broadsign Serv Inc. Method and digital signage server for managing placement of a digital signage content based on metric thresholds

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6873710B1 (en) * 2000-06-27 2005-03-29 Koninklijke Philips Electronics N.V. Method and apparatus for tuning content of information presented to an audience
US7136871B2 (en) * 2001-11-21 2006-11-14 Microsoft Corporation Methods and systems for selectively displaying advertisements
US7979877B2 (en) * 2003-12-23 2011-07-12 Intellocity Usa Inc. Advertising methods for advertising time slots and embedded objects

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See references of WO2007120686A3 *

Also Published As

Publication number Publication date
WO2007120686A2 (fr) 2007-10-25
WO2007120686A3 (fr) 2007-12-27

Similar Documents

Publication Publication Date Title
US20210326931A1 (en) Digital advertising system
CN105339969B (zh) 链接的广告
US7921036B1 (en) Method and system for dynamically targeting content based on automatic demographics and behavior analysis
US20020072952A1 (en) Visual and audible consumer reaction collection
US8725567B2 (en) Targeted advertising in brick-and-mortar establishments
JP6138930B2 (ja) デジタル看板上での表示のための広告を選択する方法および装置
US20080004951A1 (en) Web-based targeted advertising in a brick-and-mortar retail establishment using online customer information
US11636510B2 (en) Systems, methods and programmed products for dynamically tracking delivery and performance of digital advertisements in electronic digital displays
JP2008501164A (ja) 視覚刺激に基づくモバイル問合せシステムおよび方法
EP2055101A2 (fr) Distribution et adaptation automatisees de contenu multimedia
CN104012100A (zh) 作为媒体曝光计的可穿戴计算机
JP2010506263A (ja) コード誘因情報を照会及び提供するための装置、方法、およびシステム
TW202018638A (zh) 多媒體物料推送方法和裝置
US20070288486A1 (en) Methods and system for providing information
US11393048B2 (en) Location-based open social networks and incentivization methods
JP6799655B1 (ja) ユーザインタフェース方法、端末プログラム、端末装置、及び広告システム
WO2014076442A1 (fr) Installation en libre-service pour fournisseurs de contenu
JP2008269537A (ja) 関連性のある広告を供給するための方法及びシステム
CN108573056B (zh) 内容数据处理方法、装置、电子设备及存储介质
JP2002366724A (ja) マーケティング情報取得システム、マーケティング情報取得方法及びマーケティング情報取得用プログラム
WO2009074791A1 (fr) Système de signalisation
US20140040031A1 (en) Method of advertising to a targeted buyer
JP2005332343A (ja) 広告配信システム
US20220327640A1 (en) Location-Based Open Social Networks
TWM551710U (zh) 用戶資料蒐集系統

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

17P Request for examination filed

Effective date: 20090217

AK Designated contracting states

Kind code of ref document: A2

Designated state(s): AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IS IT LI LT LU LV MC MT NL PL PT RO SE SI SK TR

AX Request for extension of the european patent

Extension state: AL BA HR MK RS

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION IS DEEMED TO BE WITHDRAWN

18D Application deemed to be withdrawn

Effective date: 20101103