WO2002057959A2 - Appareil et procedes de gestion de contenus numeriques - Google Patents

Appareil et procedes de gestion de contenus numeriques Download PDF

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Publication number
WO2002057959A2
WO2002057959A2 PCT/US2002/001530 US0201530W WO02057959A2 WO 2002057959 A2 WO2002057959 A2 WO 2002057959A2 US 0201530 W US0201530 W US 0201530W WO 02057959 A2 WO02057959 A2 WO 02057959A2
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WO
WIPO (PCT)
Prior art keywords
objects
distribution
match group
computer program
program product
Prior art date
Application number
PCT/US2002/001530
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English (en)
Other versions
WO2002057959A3 (fr
Inventor
Kenneth Rothmuller
Laurie Vertelney
Michael Slater
Bernard Peuto
Original Assignee
Adobe Systems Incorporated
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
Priority claimed from US09/774,523 external-priority patent/US20020087546A1/en
Application filed by Adobe Systems Incorporated filed Critical Adobe Systems Incorporated
Publication of WO2002057959A2 publication Critical patent/WO2002057959A2/fr
Publication of WO2002057959A3 publication Critical patent/WO2002057959A3/fr

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Classifications

    • 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
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • 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
    • G06F16/54—Browsing; Visualisation therefor

Definitions

  • the present invention relates to methods and apparatus for storing, cataloguing, managing, organizing, finding and displaying objects such as digital images.
  • the invention includes methods for associating ("tagging") fields of text and numeric data ("metadata”) with individual objects such as images or photos, storing the objects and associated metadata as records in a relational database, and selecting, sorting, organizing and finding the objects based on their tagged metadata content.
  • Default metadata tags can be specified, and new metadata tags can be defined and created through a tag editor by naming the tag, selecting its tag type, optionally selecting a graphical icon that represents the tag, and filling in any remaining fields or attributes that are unique to and define the tag type.
  • Tags can be readily associated with an object by adding a record containing the tag information or metadata to a database, and relating the tagged metadata record to a database record containing the object or a pointer to the object.
  • Tags can also be graphically associated with an object by, for example, dragging and dropping a graphical icon representing the tag onto a graphical representation of the object. In the latter case, database records containing the tag metadata are automatically created and related to the database record containing the target object or a pointer to the target object.
  • these search criteria can include, but are not limited to, the date and time the photos were taken, textual information that is associated with the photos such as the names of the people who are in the photos or the places or events where the photos were taken, designations of the photos as favorite photos, and designation of the photos as photos that have been printed, shared with others, or archived on a certain date.
  • the matching objects can be viewed or arranged according to the degree to which they have associated metadata that matches the search criteria.
  • objects that match all of the search criteria can be displayed first, followed by objects that match one or more of the search criteria, and finally by objects that match none of the search criteria.
  • Objects in the different match groups can be differentiated from one another in the display area by visual cues, such as being displayed in front of different background colors or patterns.
  • objects matching all of the search criteria can be displayed in front of a white background, while objects matching some of the search criteria can be displayed in front of a blue background, and objects matching none of the search criteria can be displayed in front of a gray background.
  • the distribution of the objects stored in the database can be displayed as a histogram along a timeline.
  • Time bands can be set along the timeline to indicate a time period that can be used to search for matching objects in the database, or to limit the search results for a given tag search to objects having temporal metadata within the indicated time period.
  • the timeline displays not only the temporal distribution of all objects in the database over the indicated time period, but also the temporal distribution of all objects in the database matching the specified tag search criteria over the indicated time period.
  • the temporal distribution of objects in the database can be represented in a calendar view such that the days of the calendar indicate the number of objects having metadata associated with a given day of the week in a given week of the month.
  • the calendar view can also be used to limit the search results for a tag search, in which case the calendar view will indicate all of the days of the month associated with objects that match all of the tagged search criteria, match some of the tagged search criteria, and match none of the tagged search criteria.
  • Figs. 1 illustrates one embodiment of a user interface for a computer program product in accordance with the present invention.
  • Fig. 2 illustrates an image displayed with its associated metadata, including its tags, in accordance with the present invention.
  • Fig. 3 illustrates a timeline view of the data in accordance with the present invention.
  • Fig. 4 illustrates a calendar view of the data in accordance with the present invention.
  • Fig. 5 illustrates a map view of the data in accordance with the present invention.
  • Fig. 6 illustrates the display of different media types that are stored in accordance with the present invention.
  • the present invention provides a method for users to organize and find digital images and photos by tagging them.
  • photos Before being tagged, photos must be imported into a database where photographic metadata or information about the photos can be stored. While entire photos can be stored in the database, it is generally more efficient to store pointers to photos in the database rather than the photos themselves.
  • Photos can be imported into the database from any of a number of devices or sources including, but not limited to, a digital camera, a flash memory device, a hard disk drive, a floppy drive, a CD-ROM, or a networked computer or file server.
  • the photos Once imported into the database, the photos can be tagged with one or more objects containing metadata that identifies the unique or important properties of the photo such as when or where the photo was taken, or who or what is the subject of the photo.
  • tags 350 can be applied to photos by dragging and dropping graphical icons representing the tags onto one or more photos 1-4 that are displayed in an image area 100.
  • the database record that contains a pointer to the photo is updated to contain or point to metadata that is associated with the tag that has been dropped onto the photo.
  • This metadata can include when the photo was taken, where it was taken, the nature of the event at which it was taken, the subject of the photo, and whether the user considers the photo one of his or her favorites.
  • photos with specific tags or combinations of tags can be readily found in the database by searching the database for all records that contain the same metadata as the metadata that is associated with the one or more search tags.
  • Tags can be created and modified in a tag editor.
  • the tag editor allows a user to specify a tag name and tag type, and to enter metadata in the form of tag attributes that can be stored in tags of the specified tag type.
  • tags can be divided into one or more tag categories. For example, in one embodiment tags are divided into people, events, places and miscellaneous tag categories. Tags in the different tag categories generally have different tag attributes to distinguish between themselves and tags in other tag categories.
  • a tag's attributes do not need to be filled in to associate a tag with a photo.
  • the tag itself is a form of metadata that can be associated with the photo, regardless of whether the tag's possible attributes are also associated with the photo. However, when a tag's attributes are completely or partially filled in, more metadata is associated with the tagged photo, thereby making the photo easier to search for and find.
  • the people tag category includes default tag types for family and friends, and can be customized to include other groups of people such as business associates, classmates, co-workers, and neighbors, and particular individuals such as a spouse, daughter, or friend.
  • Tags in the people category can contain attributes such as a person's name, sex, birthdate, anniversary, postal and/or email address(es), phone number(s), a sharing profile specifying which if any pictures can be shared with the people associated with the tag, and the relationships between the people associated with the tag and other tagged individuals.
  • the events tag category includes default tag types for parties and vacations, and can be customized to include tag types for particular types of events such as concerts, plays, shows and sporting events, and for particular events such as the 2002 Boston Marathon.
  • tags in the events category can include pre-defined calendar events such as New Years Eve, and customized calendar events such as birthdays and anniversaries.
  • tags in the event tag category can contain attributes corresponding to the names, locations, and dates of the underlying events associated with the tags.
  • the places tag category can be customized to include tag types for particular places such as a home, an office, an art museum, or a vacation destination.
  • Tags in the places tag category can contain attributes corresponding to specific locations that are associated with photos, including the name of the location (e.g., The Metropolitan Opera House), the names of the city, state, country and region of the world in which the photos were taken or which are the subject of the photos, and the geographical coordinates (e.g., longitude and latitude) for those places.
  • miscellaneous tag category is as a customizable catchall for tags that cannot be easily grouped into a meaningful global category with other tags.
  • miscellaneous tag types include tags for an apartment or home search, tags for artistic or photos, and tags for particular cars or types of cars.
  • Miscellaneous tags can contain attributes corresponding to the name of the subject of the photo, and where and when the photo was taken.
  • the metadata that is associated with a photo can be viewed and edited directly by displaying the photo together with its associated metadata.
  • Fig. 2 shows a photo entitled "Lori on the road at Legoland" associated with a customized people tag, Lori R., and a customized places tag, San Diego. The tags and title indicate this is a photo of Lori R. taken on a trip to Legoland in San Diego, CA. This photo can be retrieved from the database in any number of different ways, together with different photos that are related to this photo in different ways, as discussed below.
  • photos in the database that have been tagged with one or more tags can be searched for and sorted by querying the database for all photos having tags that match one or more search tags or the metadata contained within the one or more search tags.
  • These metadata can include, but are not limited to, data indicating whether photos are favorites; frequently viewed; similar to currently selected photos; untagged; taken on a particular day or recurring event; shared with or received from certain people; imported from certain places; and printed or exported on certain dates.
  • the metadata can include the subject of the photo, whether a person, place, or event; as well as the place and/or event at which the photo was taken. For example, the photo of Lori R.
  • Legoland in Legoland can be retrieved from the database by querying the database for all photos tagged with a Lori R. tag. This search will pull up all photos of Lori R., including the Legoland photo, regardless of where the photos were taken.
  • the Legoland photo can be retrieved by searching the database for all photos tagged with a San Diego tag. This search will pull up all photos taken in or of San Diego, including the Legoland photo, regardless of who is in the photo.
  • the Legoland photo can be retrieved by searching the database for all photos tagged with both a Lori R. tag and a San Diego tag. This search will pull up all photos taken in or of San Diego that include Lori R, including the Legoland photo.
  • the database search for photos that match certain tags or groups of tags can be graphically constructed by dragging various icons representative of tags 350 into a graphical query builder or lens 220, and searching the database for records with matching tags or metadata.
  • search criteria are applied to the photos in the database, the order in which the photos are displayed is updated so that "best match” photos or photos that match all of the search criteria are displayed at the top of an image area 100 in front of a first background color or pattern, while "close match” photos that match one or more but not all of the search criteria are displayed after the "best match” photos and are visually distinguished from them by, for example, being displayed in front of a second background color or pattern, and "no match" photos that fail to match any of the search criteria are displayed at the bottom of the image area in front of a third background color or pattern.
  • the easiest search to conduct on tagged photos is a search for photos taken on a certain date, or within a certain period of time.
  • information indicating the date and time a photo was taken This information is often automatically associated with a photo when the photo is created or when the photo is scanned into a digital scanner. If the photo is created on a digital camera, the camera will generally tag the photo with the date and time the photo was taken. If the photo is scanned into a digital scanner, the scanner will generally tag the photo with the date and time it was scanned. If for any reasons neither the digital camera nor digital scanner tags the photo with the date and time information, the database will tag the photo with the information when it is first imported.
  • the temporal metadata associated with the photos can be used to present a histogram of photos in the form of a timeline 250 as shown in Fig. 1.
  • the timeline 250 can show the number of photos taken as a function of time over some period of time that can range from the time the first photo in the database was taken to the present.
  • the timeline 250 can be used by itself, or with other tags 350 to specify the criteria used to search for matching photos.
  • the timeline includes adjustable time bands 251 that can be moved to allow timeline 250 to specify the time period that is used to find matching photos.
  • the adjustable time bands 251 can be moved to find all photos in the database that are tagged with a date or timestamp that falls within the range indicated by the adjustable time bands 251. Photos falling within this range are designated "best match" photos, and can be viewed as such in image area 100.
  • the timeline 250 can be used by itself to find all photos taken between Jan. 1, 2000 and Feb. 28, 2000 by moving the adjustable time bands 251 to these two respective dates.
  • the photos in the database that have been tagged with a timestamp falling between these two dates can be retrieved from the database, and displayed in the "best match" section of image area 100.
  • the timeline 250 can be used with other metadata to limit search tag results. For example, if the adjustable time bands 251 of timeline 250 indicate the period of interest extends from Jan. 1, 2000 to Feb. 28, 2000, searching the database for all photos having a San Diego tag will return the photo "Lori on the road at Legoland” as a "best match” photo, and display the photo in image area 100, only if the photo was taken sometime between Jan. 1, 2000 and Feb. 28, 2000. If the photo was taken outside of this time period, it would only appear as a "close match" photo in image area 100.
  • the timeline displays the total number of photos in the database per unit time period in a first color which may be a solid color, and the total number of photos in the database that match the tagged search criteria as "best" or "close” matches in a second color which may be a hatched pattern or color.
  • the timeline 250 shown in Fig. 3 does not display the exact number of photos taken during a given period of time, but rather displays a vertical bar graph with bar heights that are representative of the number of photos taken during a given period of time normalized to the average number of photos taken during all such similar periods of time in the database.
  • the displayed vertical bar can have a height of 0 when no photos have been taken during that period; 1 when one to five photos have been taken during that period; 2 when the normalized number of photos taken during that period was up to 50% of the average number of photos taken during all time periods; 3 when the normalized number of photos taken during that period was between 50% and 80% of the average number of photos taken during all time periods; 4 when the normalized number of photos taken during that period was between 80% and 120% of the average number of photos taken during all time periods; 5 when the normalized number of photos taken during that period was between 120% and 150% of the average number of photos taken during all time periods; 6 when the normalized number of photos taken during that period was between 150% and 200% of the average number of photos taken during all time periods; and 7 when the normalized number of photos taken during that period was more than 200% of the average number of photos taken during all time periods.
  • photos taken on a particular day or during a particular month can also be found by displaying the photos in a 2-D histogram or scatter plot such as the calendar view shown in the figure.
  • the calendar view displays all of the photos that have been taken, scanned, or imported into the database on any day in a given month as a function of the day of the week the photos were taken, and the week in the month. If a particular day of the month is selected in the calendar view, all photos taken on that day can be retrieved from the database as "best match" photos.
  • Fig. 3 shows that during the month of June, 2001 two sets of photos were taken. The first set contains a single photo taken on June 8, while the second set contains 10 photos taken on June 18. By selecting the June 18 calendar day, the 10 photos taken on June 18 are selected as the "best match" photos, and can be displayed in image area 100.
  • the calendar view can also display the results of a tag search in the month-at- a-glance mode.
  • each day in the calendar can indicate not only whether any photos were taken on that day, but whether the photos taken on that day fall into the "best match", "close match”, or "no match” group with respect to the tagged search criteria. For example, if the Legoland photo described in Fig. 2 was one often photos of Lori R. taken in San Diego on June 18, 2001, and a search were done for all photos having a San Diego tag, then the June 18, 2001 square in Fig. 3 would indicate that day as having photos in the "best match” group. If, however, a search were done for all photos having a New York tag, the June 18, 2001 square in Fig.
  • calendar days containing one or more photos in the "best match” group can be presented as white squares
  • calendar days containing one or more photos in the "close match” group and no photos in the "best match” group can be presented as blue squares
  • calendar days containing no photos in either the "best match” or "close match” groups can be presented as gray squares.
  • data can be searched for and displayed in an alternate 2-D histogram or scatter plot such as a map view.
  • the place tag metadata is used to display the geographic distribution of photos in the database.
  • the map view can be used to search for photos either by itself, or in conjunction with one or more tag searches. If the map view is used by itself to search for photos, icons representing the places where photos in the database have been taken are displayed on a map such as the world map shown in Fig. 5. When a location on the map is selected, photos taken in that location can be retrieved from the database as photos in the "best match" group. For example, if the location of Kenya on the map in Fig. 5 is selected, photos taken in Kenya can be selected from the database, and can be displayed in image area 100 as "best match" photos.
  • the map view can also be used in conjunction with a tag search.
  • the map view will display not only the distribution of photos as a function of geographic location, but whether the photos taken at the various geographic locations fall in the "best match", "close match”, or "no match” group with respect to the tagged search criteria. For example, if a search for all photos having an African tag were displayed in the map view, the map view would indicate that photos taken from the Kenya Safari fall into the "best match” group, while all of the other photos shown in Fig. 5 fall into the "no match” group.
  • the particular group into which a set of photos taken from a given location falls can be indicated on the map using the same color based indication scheme used to indicate matching photo groups that are displayed in image area 100.
  • locations containing one or more photos in the "best match” group can be presented as a white area
  • locations containing one or more photos in the "close match” group and no photos in the "best match” group can be presented as a blue area
  • locations containing no photos in either the "best match” or "close match” groups can be presented as a gray area.
  • the map view can be varied in size and shape to accommodate the geographic extent of the photos that are either in the database or that are responsive to a tag search conducted on the photos in the database. Thus, if a map view is used to display or further search among database photos having a North American tag, the map view can be limited to a view of the North American continent.
  • the map view can also be varied in size and shape by selecting particular regions of a map, such as the western region of the United States, or by zooming in and out of the currently displayed map region. Photos corresponding to particular locations within a map view, like San Diego, can be geographically found directly from the map view.
  • photos matching a given set of tags can be selected as a group, and various photo management functions such as printing, sharing, or exporting the photos to a slide show or to a photo album can be performed on the group.
  • various photo management functions such as printing, sharing, or exporting the photos to a slide show or to a photo album can be performed on the group.
  • all photos in the "best match” group are selected when selecting photos that match a given set of tag search criteria.
  • the default can be changed such that all photos in both the "close match” and "best match” groups are selected when selecting photos that match a given set of tag search criteria.
  • the invention can equally be used to manage, catalogue, search for and find other types of digital media such as video files, audio files, photo slide shows, and photo albums.
  • These different types of media can be distinguished from one another with a tag of tag type media.
  • the media tag when applied to a media object, can graphically indicate the type of media object that is stored in the database.
  • a video file 600 can be stored in the database and identified by displaying its first frame together with an overlaid video file icon.
  • an audio file 610 can be stored in the database and identified by displaying the title of the audio file together with an audio file icon. Audio files can be associated with and stored as a component part of a slide show or photo album, and can be played as a soundtrack whenever the slide show or photo album is viewed. Slide shows such as slide show 620, and photo albums such as photo album 630 can also be stored in the database, and iconically identified as shown Fig. 6. Each of these objects can be tagged, searched for, and manipulated using the same tools that are used to tag, search for, and manipulate digital photos, as previously discussed.
  • Apparatus of the invention can be implemented in a computer program product tangibly embodied in a machine-readable storage device for execution by a programmable processor; and method steps of the invention can be performed by a programmable processor executing a program of instructions to perform functions of the invention by operating on input data and generating output.
  • the invention can be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and at least one output device.
  • Each computer program can be implemented in a high-level procedural or object-oriented programming language, or in assembly or machine language if desired; and in any case, the language can be a compiled or interpreted language.
  • Suitable processors can include both general and special purpose microprocessors.
  • a processor will receive instructions and data from a read-only memory and/or a random access memory.
  • a computer will include one or more mass storage devices for storing data files; such devices include magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and optical disks.
  • Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non- volatile memory, including by way of example semiconductor memory devices, such as EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM disks. Any of the foregoing can be supplemented by, or incorporated in, application-specific integrated circuits (ASICs).
  • semiconductor memory devices such as EPROM, EEPROM, and flash memory devices
  • magnetic disks such as internal hard disks and removable disks
  • magneto-optical disks and CD-ROM disks.
  • CD-ROM disks CD-ROM disks

Abstract

Cette invention concerne des procédés et un appareil permettant de gérer, de trouver et d'afficher des objets, tels que des images numériques. Les objets sont étiquetés ('associés') avec des données descriptives textuelles et numériques ('métadonnées'), et sont stockés dans une base de données relationnelle à partir de laquelle les objets peuvent être choisis, triés et extraits. Les étiquettes peuvent être définies par nom, par type et selon les attributs associés. Les objets peuvent être étiquetés en déposant une étiquette sur l'objet, ou en associant un enregistrement de base de données pour l'étiquette à un enregistrement de base de données pour l'objet. Les objets étiquetés peuvent être recherchés et affichés en fonction du degré de correspondance de leurs métadonnées avec le critère de recherche. Des signaux visuels peuvent indiquer si les objets affichés correspondent à tous les critères de recherche, à certains critères, ou à aucun des critères. Des distributions d'objets de bases de données peuvent être affichées sous la forme d'histogrammes ou de diagrammes de dispersion, comprenant des lignes de temps, des calendriers ou des cartes. Les distributions d'objets peuvent être utilisées pour rechercher des objets ou pour limiter les résultats de recherche d'une précédente recherche.
PCT/US2002/001530 2001-01-16 2002-01-16 Appareil et procedes de gestion de contenus numeriques WO2002057959A2 (fr)

Applications Claiming Priority (8)

Application Number Priority Date Filing Date Title
US26189701P 2001-01-16 2001-01-16
US60/261,897 2001-01-16
US17937901P 2001-01-31 2001-01-31
US09/774,523 2001-01-31
US09/774,523 US20020087546A1 (en) 2000-01-31 2001-01-31 Apparatus, methods, and systems for digital photo management
US60/179,379 2001-01-31
US99741201A 2001-11-30 2001-11-30
US09/997,412 2001-11-30

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WO2002057959A2 true WO2002057959A2 (fr) 2002-07-25
WO2002057959A3 WO2002057959A3 (fr) 2003-03-06

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