Direct Annotation:
`A Drag-and-Drop Strategy for Labeling Photos
`
`Ben Shneiderman, Hyunmo Kang
`Dept. of Computer Science, Human-Computer Interaction Laboratory,
`Institute for Advanced Computer Studies & Institute for Systems Research
`University of Maryland, College Park, MD 20742 USA
`{ben, kang}@cs.umd.edu
`
`Abstract
`Annotating photos is such a time-consuming, tedious
`and error-prone data entry task that it discourages most
`owners of personal photo libraries. By allowing users to
`drag labels such as personal names from a scrolling list
`and drop them on a photo, we believe we can make the
`task faster, easier and more appealing. Since the names
`are entered in a database, searching for all photos of a
`friend or family member is dramatically simplified. We
`describe the user interface design and the database
`schema to support direct annotation, as implemented in
`our PhotoFinder prototype.
`Keywords: direct annotation, direct manipulation,
`graphical user interfaces, photo libraries, drag-and-drop,
`label placement
`
`1. Introduction
`
`Adding captions to photos is a time-consuming and
`error prone task for professional photographers, editors,
`librarians,
`curators,
`scholars,
`and
`amateur
`photographers.
` In many professional applications,
`photos are worthless unless they are accurately described
`by date, time, location, photographer, title, recognizable
`people, etc. Additional annotation may include details
`about the photo (for example, film type, print size,
`aperture, shutter speed, owner, copyright information)
`and its contents (keywords from controlled vocabularies,
`topics from a hierarchy, free text descriptions, etc.). For
`amateur photographers, annotations are rarely done,
`except for the occasional handwritten note on the back of
`a photo or an envelope containing a collection of photos.
`For those who are serious about adding annotations,
`the common computer-based approach is to use database
`programs, such as Microsoft Access, that offer form fill-
`in or free text boxes and then store the information in a
`database. Data entry is typically done by typing, but
`selecting attribute values for some fields (for example,
`black&white or color film) is supported in many systems.
`
`Of course, simpler tools that provide free-form input,
`such as word processors, spreadsheets, and other tools are
`used in many situations. Captions and annotations are
`often displayed near a photo on screen displays, web
`pages, and printed versions. Software packages (Kodak
`PhotoEasy, MGI PhotoSuite, Aladdin Image AXS, etc.)
`and web sites (Kodak’s photonet, Gatherround.com,
`shutterfly, etc.) offer modest facilities to typing in
`annotations and searching descriptions.
`As photo library sizes increase the need and benefit of
`annotation and search capabilities grows. The need to
`rapidly locate photos of Bill Clinton meeting with Boris
`Yeltsin at a European summit held in 1998 is strong
`enough to justify substantial efforts in many news
`agencies. More difficult searches such as “agriculture in
`developing nations” are harder to satisfy, but many web
`and database search tools support such searches (Lycos,
`Corbis, etc.). Query-By-Image-Content from IBM, is one
`of many projects that uses automated techniques to
`analyze
`image
`(http://wwwqbic.almaden.ibm.com/).
`Computer vision techniques can be helpful in finding
`photos by color (sunsets are a
`typical example),
`identifying features (corporate logos or the Washington
`Monument), or textures (such as clouds or trees), but a
`blend of automated and manual techniques may be
`preferable. Face recognition research offers hope for
`automated annotation, but commercial progress is slow
`[1][2].
`
`2. Related Work on Annotation
`
`Annotation of photos is a variation on previously
`explored problems such as annotation on maps [3][4][5]
`in which the challenge is to place city, state, river, or
`lake labels close to the features. There is a long history
`of work on this problem, but new possibilities emerge
`because of the dynamics of the computer screen (Figure
`1). However, annotation is usually seen as an authoring
`process conducted by specialists and users only chose
`
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`

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`whether to show or hide annotations. Variations on
`annotation also come from the placement of labels on
`markers in information visualization tasks such as in tree
`structures, such in the hyperbolic tree [6] (Figure 2) or in
`medical histories, such as LifeLines [7] (Figure 3).
`
`Figure 1. US Map with City Names
`
`Figure 2. Hyperbolic Tree
`
`Figure 3. LifeLines Medical Patient History
`Previous work on annotation focused on writing
`programs to make label placements that reduced overlaps
`[8], but there are many situations in which it is helpful
`for users to place labels manually, much like post-it
`notes, on documents, photos, maps, diagrams, webpages,
`etc. Annotation of paper and electronic documents by
`hand is also a much-studied topic with continuing
`innovations [9]. While many systems allow notes to be
`placed on a document or object, the demands of
`annotating personal photo libraries are worthy of special
`study [10]. We believe that personal photo libraries are a
`special case because users are concentrating on the
`photos (and may have a low interested in the underlying
`technology), are concerned about the social aspects of
`sharing photos, and are intermittent users. They seek
`enjoyment and have little patience for form filling or data
`entry.
`
`3. The PhotoFinder Project
`
`In the initial stages of our project on storage and
`retrieval
`from
`personal
`photo
`libraries
`(http://www.cs.umd.edu/hcil/photolib/), we emphasize
`collection management and annotation
`to support
`searching for people. This decision was based on our
`user needs assessment, reports from other researchers,
`and our personal experience that indicate that people
`often want to find photos of a friend or relative at some
`event that occurred recently or years ago [2][11].
`Personal photo libraries may have from hundreds to tens
`of thousands of photos, and organization is, to be
`generous, haphazard. Photos are sometimes in neat
`albums, but more often put in a drawer or a shoebox.
`While recent photos are often on top, shuffling through
`the photos often leaves them disorganized. Some users
`will keep photos in the envelopes they got from the photo
`store, and more organized types will label and order
`them.
`
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`Exhibit 1016
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`As digital cameras become widespread, users have
`to
`improvise organization
`strategies using
`had
`hierarchical directory
`structures,
`and
`typing
`in
`descriptive file and directory names to replace the
`automatically generated photo file numbers. Some
`software packages (PhotoSuite, PhotoEasy, etc.) enable
`users to organize photos into albums and create web
`pages with photos, but annotation is often impossible or
`made difficult. Web sites such as Kodak’s Photo.net,
`Gatherround.com, etc. enable users to store collections of
`photos and have discussion groups about the collections,
`but annotation is limited to typing into a caption field.
`The pioneering effort of the FotoFile [2] offered an
`excellent prototype that inspired our work.
`Our goal in the PhotoFinder project was to support
`personal photo library users. We developed a conceptual
`model of a library having a set of collections, with each
`collection having a set of photos. Photos can participate
`in multiple collections. Collections and individual
`photos can be annotated with free text fields plus date
`and location fields stored in a database (see Figure 6 for
`our Photo Library database schema). Our interface has
`three main windows:
`
` Library viewer: Shows a representative photo for
` Collection viewer: Shows thumbnails of all photos
`
`each collection, with a stack representing the number
`of photos in each collection.
`
`in the collection. Users can move the photos around,
`enlarge them all or individually, cluster them, or
`present them in a compact manner. A variety of
`
`thumbnail designs were prototyped and will be
`refined for inclusion in future versions.
`
` Photo viewer: Shows an individual photo in a
`
`resizable window. A group of photos can be selected
`in the Collection viewer and dragged to the Photo
`viewer to produce an animated slide show.
`We also put a strong emphasis on recording and
`searching by the names of people in each photo. We
`believed that a personal photo library might contain
`repeated images of the same people at different events,
`and estimated 100-200 identifiable people in 10,000
`photos. Furthermore we expected a highly skewed
`distribution with immediate family members and close
`friends appearing very frequently. The many-to-many
`relationship between photos and people is mediated by
`the Appearance relation (Figure 6) that stores the
`identification of all the people who appear in each photo.
`Such a database would support accurate storage of
`information, but we recognized that the tedious data
`entry problem would prevent most users from typing in
`names for each photo. Furthermore, the inconsistency in
`names is quickly a problem with misspellings or variant
`names (for example, Bill, Billy, William) undermining
`the success of search.
`A second challenge we faced was that the list of
`names of people appearing in a photo could often be
`difficult to associate with individuals, especially in group
`shots.
` Textual captions often indicate left-to-right
`ordering in front and back rows, or give even more
`specific identification of who is where.
`
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`Figure 4. PhotoFinder1 display with Library Viewer on the left, Collection Viewer with thumbnails
`on the upper right, and Photo Viewer on the lower right.
`
`4. Direct Annotation
`
`To cope with these challenges we developed the
`concept of direct annotation: selectable, dragable labels
`that can be placed directly on the photo. Users can select
`from a scrolling or pop-up list and drag by mouse or
`touch screen. This applies direct manipulation principles
`[12] that avoid the use of a keyboard, except to enter a
`name the first time it appears. The name labels can be
`moved or hidden, and their presence is recorded in the
`database in the Appearance relation with an X-Y
`
`location, based on an origin in the upper left hand corner
`of the photo.
`This simple rapid process also allows users to annotate at
`will. They can add annotations when they first see their
`photos on the screen, when they review them and make
`selections, or when they are showing them to others.
`This easy design and continuous annotation facility may
`encourage users to do more annotation. Figures 5 (a)-(f)
`show the process of annotation on a set of four people at
`a conference.
`
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`Exhibit 1016
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`

`

` (a) Initial State
`
` (c) Dragging
`
` (e) Four Identified People
`
`
`
`
`
`
`
`
`
` (b) Select Name
`
` (d) Dropped
`
` (f) Hide Annotations
`
`Figure 5. The Process of Dragging and Dropping an Annotation on a Photo
`The selection list is shown as being an alphabetically
`stored. The tone gives further feedback and reinforces
`organized scrolling menu, but it could be implemented as
`the sense of accomplishment. Further reinforcement for
`a split menu [13]. This would entail having 3-5 of the
`annotation is given by subtly changing the border of
`most commonly occurring names in a box, followed by
`photos in the Collection viewer. When a photo gets an
`the alphabetical presentation of the full list. Thus the
`annotation, its thumbnail’s white border changes to
`most frequent names would be always visible to allow
`green. Users will then be able to see how much they
`rapid selection. Name completion strategies for rapid
`have accomplished and which photos are still in need of
`table navigation would be useful in this application.
`annotation.
`When users mouse down on a name, the dragging begins
`A Show/Hide checkbox gives users control over seeing
`and a colored box surrounds the name. When users
`the photo with and without the name labels. Since the
`mouse up, the name label is fixed in place, a tone is
`photo viewer window is resizable, the position of the
`sounded, and the database entry of the XY coordinates is
`labels changes to make sure they remain over the same
`
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`

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`person. A small marker (ten pixels long) hangs down
`from the center of the label to allow precise placement
`when there are many people close together. The marker
`can be used to point at the head or body and it becomes
`especially useful in crowded group photos.
`Future additions might include the capacity to resize
`the
`labels, change
`fonts, change colors, or add
`animations. Another interesting issue is collaborative
`annotation in which multiple users working side-by-side
`[14] or independently might annotate photos and then the
`results could be combined, with appropriate resolution of
`conflicts. Tools for finding variant spellings or switches
`between last and first names would help raise data
`quality. A valuable accelerator is bulk annotation [2], in
`which a group of photos is selected and then the same
`label is applied to every photo with one action, although
`individual placement might still be needed.
`Of course, annotation by names of people in photos is
`only the first step. Drag and drop annotation for any
`kind of object in a photo (car, house, bicycle), map
`(cities, states, lakes), or painting (brushstroke, signature,
`feature) is possible. Annotation about the overall image,
`such as type of photo (portrait, group, landscape), map
`(highway,
`topographic,
`urban),
`or
`painting
`(impressionist, abstract, portrait) is possible. Colored
`ribbons or multiple star icons could be used to indicate
`the importance or quality of photos.
`Searching and browsing become more effective once
`annotations are included in the photo database. The
`obvious task is to see all photos that include an
`individual. This has been implemented by simply
`dragging the name from the list into the Collection
`viewer or to a designated label area. The PhotoFinder
`finds and displays all photos in which that name appears
`in a label.
`
`5. Database Design and Implementation
`
`5.1 Schema of the Photo Library database
`
`The PhotoFinder operates using a Photo Library
`database (Microsoft Access), which contains five linked
`tables (Figure 6). The basic concept is that a Photo
`Library contains Collections of Photos, and that Photos
`contain images of People.
`In the Photo Library schema, the Collections table
`represents the collections of photos with attributes such
`as Collection Title, Description, Keywords, Starting
`Date, Ending Date, Location, Representative PhotoID
`and unique Collection ID. The Photos table is where
`references (full path and file name) of photos and their
`thumbnails are stored with important attributes such as
`the date of photo, event, keywords, location, rating, color,
`locale, and so on. Each photo should have a unique
`reference and photos with the same references are not
`allowed to be stored in this table even though they have
`different attribute values. The Linkage table is the
`connection between the Collections table and Photos
`table. It stores the links between collections and photos.
`The People table stores all the information about the
`people who appear in the Photo Library. In our initial
`implementation, attributes include only the Given (First)
`name and Family (Last) name of the person, and the
`unique PersonID (people with the same first and last
`name are not allowed to be stored in People table).
`Eventually, the People table will be extended to include
`personal
`information such as e-mail address
`for
`exporting
`the Photo Library, homepage address,
`occupation and so on. The Appearance table stores the
`information about which Person is in which Photo. It
`serves as the linkage between the Photos table and the
`People
`table. Attributes
`include AppearanceID,
`PersonID, PhotoID, and relative (X, Y) coordinates
`(upper left corner is (0,0), lower right is (100,100)) of
`people in the photos.
`In designing the Photo Library, we made three major
`assumptions concerning the Library, Collections, and
`Photos. These assumptions can be classified as follows:
`
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`Figure 6. The schema of Photo Library database
`
`A 1-to-many relationship between the Collections
`table and the Linkage table has been set so that a
`collection can contain multiple photos, and a 1-to-many
`relationship between the Photos table and the Linkage
`table has been set so that same photo can be included in
`multiple collections. It is also possible that a collection
`contains the same photo multiple times to permit
`reappearances in a slide presentation. Two different
`collections could have exactly same set of photos. If two
`photos have different path names, they are different
`photos even though they are copies of a photo.
`
` Relationship between Collections and Photos
` Relationship between Photos and People
` Relationship among Library, Collections, and
`
`A 1-to-many relationship between the Photos table
`and the Appearance table has been set so that a photo can
`contain multiple persons, and a 1-to-many relationship
`between People table and Appearance table has been set
`so that same person can be included in multiple photos.
`Multiple appearances of the same person in a photo are
`not allowed. A composite pair of Given name and Family
`name should be unique in the People table.
`
`Photos
`Within a library, the same photo could be contained in
`multiple collections multiple times, but their attributes
`and annotations must be the same.
`
`In the first design of the Photo Library database, we
`only considered annotation by names of people in photos,
`but the Photo Library database can be easily extended by
`adding an Object table, Animal table, Keyword table, and
`so on, along with connection tables similar to the
`
`Appearance table. With such a Photo Library database
`design, more flexible annotation would be possible.
`5.2 Updating the Photo Library Database by
`Direct Annotation
`
`the Photo Library
`PhotoFinder keeps updating
`database whenever the direct annotation module causes
`any information changes. In this section, we classify the
`Photo Library database updating situations into five
`categories, and discuss corresponding algorithm and
`implementation issues.
`
` Adding a New Name Label / Creating a New Person:
`
`When users drag a name from "People in Library"
`listbox and drop
`it onto a photo, PhotoFinder
`immediately checks whether there already exists an
`Appearance connection between the photo and the person
`since multiple appearances of the same person in a photo
`are not allowed. If a conflict occurs, PhotoFinder would
`highlight the existing name label on the photo and ignore
`the drag-and-drop event with a warning message. If there
`is no conflict, PhotoFinder finds the PersonID and
`PhotoID, calculates a relative (X, Y) position (0£
` X, Y
`£ 100) of the drag-and-drop point on the photo, and then
`creates a new Appearance record with this information.
`After adding a new record to the Appearance table, the
`PhotoFinder updates "People in this Photo" listbox and
`finally creates a name label on the photo. To show that
`the label has just been inserted, the newly added name in
`the "People in this Photo" listbox will be selected, and
`accordingly the new name label on the photo will be
`highlighted. If the added name label is the first one on
`the photo, PhotoFinder sends an event to the Collection
`Viewer to change the border color of the corresponding
`thumbnail to green, in order to show that the photo now
`
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`

`has an annotation. The algorithm for creating a new
`person is simple. As soon as users type in the first name
`and last name of a person in the editbox and press enter,
`PhotoFinder checks whether the name already exists in
`the People table. If so, a warning message will be
`displayed with the name in "People in Library" listbox
`being selected. If not, PhotoFinder creates and adds a
`new Person record to the People table, and then updates
`the
`"People
`in Library"
`listbox,
`selecting
`and
`highlighting the newly added name.
`
`from the center of the label to allow precise placement.
`But since the size and direction (downward) of the
`marker is fixed, it is somewhat difficult to distinguish
`labels when many people appear in the photo close
`together. Using Excentric labels [15] or adding an
`additional (X, Y) field to the Appearance table to allow a
`longer and directional marker could solve this problem.
`Other features such as changing the font size of labels
`and avoiding occlusion among labels in resizing the
`photo will be handled in future versions of PhotoFinder.
`
` Deleting Name Label / Deleting Person:
`
`When the delete button of the Photo Viewer toolbar is
`clicked or the delete key is pressed, PhotoFinder checks
`whether the selected name label already exists. If not,
`PhotoFinder ignores the deleting action. But if it exists,
`PhotoFinder automatically calculates the PersonID of the
`selected name label and the PhotoID, and it searches
`through the Appearance table to find and delete an
`Appearance record having
`those IDs. PhotoFinder
`updates "People in this Photo" listbox and deletes the
`name label on the photo. If the deleted name label was
`the last one on the photo, PhotoFinder sends an event to
`the Collection Viewer to change the border color of the
`corresponding thumbnail to white, to show that the photo
`has no annotation. If focus is on the "People in Library"
`listbox and the delete key is pressed, PhotoFinder finds
`the PersonID of the selected name in the listbox.
`PhotoFinder deletes the PersonID from the People table
`and also deletes all the Appearance records containing
`that PersonID, which results in the complete elimination
`of the name label from the other photos in the Photo
`Library. Again, Collection Viewer updates the border
`color of thumbnails that no longer have annotations.
`
`Users can edit a name of person in library by pressing
`the edit button of the Photo Viewer toolbar or by just
`double clicking over the selected name in the "People in
`Library" listbox. When the edited name is typed in,
`PhotoFinder finds and changes the corresponding person
`record from the People table only if there is no
`duplication of the name in the People table. It also
`refreshes both the "People in this Photo" and the “People
`in Library” listboxes, and all the name labels on the
`current photo. If duplication occurs, the whole editing
`process will be ignored with a warning message.
`
` Editing a Name of Person:
` Positioning Name Label:
`
`Drag-and-dropping the existing label over the photo
`can change position of the name label. As mentioned
`before, the relative (X, Y) position of the center point of a
`name label is stored in the corresponding Appearance
`record. PhotoFinder uses a small marker hanging down
`
`
`
`Importing People Table from other Libraries:
`Retyping the names that already exist in other
`libraries is very tedious and time consuming
`job.
`Therefore, PhotoFinder supports a function to import the
`People table from other libraries. The internal process of
`importing the People table is similar to that of creating a
`new person repeatedly. The only thing PhotoFinder
`should handle
`is checking and eliminating
`the
`duplication of a person name.
`
`6. Conclusion
`
`Digital photography is growing rapidly, and with it
`the need to organize, manage, annotate, browse and
`search growing libraries of photos. While numerous
`tools offer collection or album management, we believe
`that the addition of easy to use and enjoyable annotation
`techniques is an important contribution. After a single
`demonstration, most users understand direct annotation
`and are eager to use it. We are adding features,
`integrating search functions, and conducting usability
`tests.
`
`Acknowledgements: We appreciate the partial support
`of Intel and Microsoft, and the contributions of Ben
`Bederson, Todd Carlough, Manav Kher, Catherine
`Plaisant, and other members of the Human-Computer
`Interaction Laboratory at the University of Maryland.
`
`7. REFERENCES
`
`[1] R. Chellappa, C.L. Wilson and S. Sirohey, "Human
`and Machine Recognition of Faces: A Survey"
`Proceedings of the IEEE, Vol. 83, pp. 705-740, May
`1995.
`[2] Allan Kuchinsky, Celine Pering, Michael L. Creech,
`Dennis Freeze, Bill Serra, Jacek Gwizdka, “FotoFile:
`A Consumer Multimedia Organization and Retrieval
`System”, Proceedings of ACM CHI99 Conference on
`Human Factors in Computing Systems, 496-503,
`1999.
`
`Meta Platforms, Inc.
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`Page 008
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`

`

`[3] E. Imhof, “Positioning Names on Maps”, The
`American Cartographer, 2, 128-144, 1975.
`[4] J. Christensen, J. Marks, and S. Shieber, “An
`Empirical Study Of Algorithms For Point-Feature
`Label Placement”, ACM Transactions on Graphics
`14, 3, 203-232, 1995.
`[5] J. S. Doerschler and H. Freeman, “A Rule-Based
`System For Dense-Map Name Placement”,
`Communications Of The ACM 35, 1, 68-79, 1992.
`[6] John Lamping, Ramana Rao, and Peter Pirolli, “A
`Focus + Context Technique Based On Hyperbolic
`Geometry For Visualizing Large Hierarchies”,
`Proceedings of ACM CHI95 Conference on Human
`Factors in Computing Systems, New York, 401-408,
`1995.
`[7] Jia Li., Catherine Plaisant, Ben Shneiderman, “Data
`Object and Label Placement
`for
`Information
`Abundant Visualizations” Workshop on New
`Paradigms
`in
`Information Visualization and
`Manipulation (NPIV'98), ACM, New York, 41-48,
`1998.
`[8] Mark D. Pritt, “Method and Apparatus for The
`Placement of Annotations on A Display without
`Overlap”, US Patent 5689717, 1997.
`[9] Bill N. Schilit, Gene Golovchinsky, and Morgan N.
`Price, “Beyond Paper: Supporting Active Reading
`
`Ink Annotations”,
`with Free Form Digital
`Proceedings of ACM CHI 98 Conference on Human
`Factors in Computing Systems, v.1 249-256, 1998.
`[10] J Kelly Lee and Dana Whitney Wolcott, “Method of
`Customer Photoprint Annotation”, US Patent
`5757466, 1998.
`[11] Richard Chalfen, Snapshot Versions of Life, Bowling
`Green State University Popular Press, Ohio, 1987.
`[12] Ben Shneiderman, Designing the User Interface:
`Strategies
`for
`Effective
`Human-Computer
`Interaction, 3rd Edition, Addison Wesley Longman,
`Reading, MA, 1998.
`[13] Andrew Sears and Ben Shneiderman, “Split Menus:
`Effectively Using Selection Frequency To Organize
`Menus”, ACM Transactions on Computer-Human
`Interaction 1, 1, 27-51, 1994.
`[14] J. Stewart, B. B. Bederson, & A. Druin, “Single
`Display Groupware: A Model
`for Co-Present
`Collaboration.”, Proceedings of ACM CHI99
`Conference on Human Factors
`in Computing
`Systems, 286-293, 1999.
`[15] Jean-Daniel Fekete Catherine Plaisant, “Excentric
`Labeling: Dynamic Neighborhood Labeling for Data
`Visualization.”, Proceedings of ACM CHI99
`Conference on Human Factors
`in Computing
`Systems, 512-519, 1999.
`
`Meta Platforms, Inc.
`Exhibit 1016
`Page 009
`
`

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