In this paper we present and discuss the findings of a study that investigated how people manage their collections of digital photographs. The six-month, 13-participant study included interviews, questionnaires, and analysis of usage statistics gathered from an instrumented digital photograph management tool called Shoebox. Alongside simple browsing features such as folders, thumbnails and timelines, Shoebox has some advanced multimedia features: contentbased image retrieval and speech recognition applied to voice annotations. Our results suggest that participants found their digital photos much easier to manage than their non-digital ones, but that this advantage was almost entirely due to the simple browsing features. The advanced features were not used very often and their perceived utility was low. These results should help to inform the design of improved tools for managing personal digital photographs.

Eleven PC-owning families were interviewed at home about their use of conventional and digital photos. They also completed photo diaries and recorded photo-sharing conversations that occurred spontaneously over a three month period after the in-home interviews. From an analysis of the resulting materials we illustrate the strengths and weaknesses of past and present technology for photo sharing. These allow us to prioritise user requirements for a range of future photo-sharing technologies or ‘photoware’.

Why do people tag? Users have mostly avoided annotating media such as photos – both in desktop and mobile environments – despite the many potential uses for annotations, including recall and retrieval. We investigate the incentives for annotation in Flickr, a popular web-based photo-sharing system, and ZoneTag, a cameraphone photo capture and annotation tool that uploads images to Flickr. In Flickr, annotation (as textual tags) serves both personal and social purposes, increasing incentives for tagging and resulting in a relatively high number of annotations. ZoneTag, in turn, makes it easier to tag cameraphone photos that are uploaded to Flickr by allowing annotation and suggesting relevant tags immediately after capture. A qualitative study of ZoneTag/Flickr users exposed various tagging patterns and emerging motivations for photo annotation. We offer a taxonomy of motivations for annotation in this system along two dimensions (sociality and function), and explore the various factors that people consider when tagging their photos. Our findings suggest implications for the design of digital photo organization and sharing applications, as well as other applications that incorporate user-based annotation.

We developed two photo browsers for collections with thousands of time-stamped digital images. Modern digital cameras record photo shoot times, and semantically related photos tend to occur in bursts. Our browsers exploit the timing information to structure the collections and to automatically generate meaningful summaries. The browsers differ in how users navigate and view the structured collections. We conducted user studies to compare the two browsers and a commercial image browser. Our results show that exploiting the time dimension and appropriately summarizing collections can lead to significant improvements. For example, for one task category, one of our browsers enabled a 33% improvement in speed of finding given images compared to the commercial browser. Similarly, users were able to complete 29 % more tasks when using this same browser. Keywords Photo browser, image browser, Personal Digital library, time-based clustering, ACDSee, summarization, time-based navigation, burst identification 1.

This paper presents Photo Table Of Contents (PhotoTOC), a system that helps users find digital photographs in their own collection of photographs. PhotoTOC is a browsing user interface that uses an overview+detail design. The detail view is a temporally ordered list of all of the user's photographs. The overview of the user's collection is automatically generated by an image clustering algorithm, which clusters on the creation time and the color of the photographs. PhotoTOC was tested on users' own photographs against three other browsers. Searching for images with PhotoTOC was subjectively rated easier than all of the other browsers. This result shows that automatic organization of personal photographs facilitates efficient and satisfying search.

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, loc...

Consumers need help finding digital photographs in their personal collections. AutoAlbum helps users find their photos by automatically clustering photos into albums. The albums are presented in an easy-to-use browsing user interface. AutoAlbum uses the time and order of photo creation to assist in clustering: albums consist of temporally contiguous photos. The content-based clustering algorithm is best-first probabilistic model merging, which is fast and yields clusters that are often semantically meaningful.

In a hypermedia authoring task, an author often wants to set up meaningful connections between different media, such as text and photographs. To facilitate this task, it is helpful to have a software agent dynamically adapt the presentation of a media database to the user's authoring activities, and look for opportunities for annotation and retrieval. However, potential connections are often missed because of differences in vocabulary or semantic connections that are "obvious" to people but that might not be explicit. In a hypermedia authoring task, an author often wants to set up meaningful connections between different media, such as text and photographs. To facilitate this task, it is helpful to have a software agent dynamically adapt the presentation of a media database to the user's authoring activities, and look for opportunities for annotation and retrieval. However, potential connections are often missed because of differences in vocabulary or semantic connections that are "obvious" to people but that might not be explicit. ARIA (Annotation and Retrieval Integration Agent) is a software agent that acts an assistant to a user writing e-mail or Web pages. As the user types a story, it does continuous retrieval and ranking on a photo database. It can use descriptions in the story to semi-automatically annotate pictures. To improve the associations beyond simple keyword matching, we use natural language parsing techniques to extract important roles played by text, such as "who, what, where, when". Since many of the photos depict common everyday situations such as weddings or recitals, we use a common sense knowledge base, Open Mind, to fill in semantic gaps that might otherwise prevent successful associations.

Our system suggests likely identity labels for photographs in a personal photo collection. Instead of using face recognition techniques, the system leverages automatically available context, like the time and location where the photos were taken. Based on time and location, the system automatically computes event and location groupings of photos. As the user annotates some of the identities of people in their collection, patterns of re-occurrence and co-occurrence of different people in different locations and events emerge. The system uses these patterns to generate label suggestions for identities that were not yet annotated. These suggestions can greatly accelerate the process of manual annotation and improve the quality of retrieval from the collection. We obtained ground-truth identity annotation for four different photo albums, and used them to test our system. The system proved effective, making very accurate label suggestions, even when the number of suggestions for each photo was limited to five names, and even when only a small subset of the photos was annotated.

Interactive tables can enhance small-group colocated collaborative work in many domains. One application enabled by this new technology is copresent, collaborative search for digital content. For example, a group of students could sit around an interactive table and search for digital images to use in a report. We have developed TeamSearch, an application that enables this type of activity by supporting group specification of Boolean-style queries. We explore whether TeamSearch should consider all group members ’ activities as contributing to a single query or should interpret them as separate, parallel search requests. The results reveal that both strategies are similarly efficient, but that collective query formation has advantages in terms of enhancing group collaboration and awareness, allowing users to bootstrap query-specification skills, and personal preference. This suggests that team-centric UIs may offer benefits beyond the “staples ” of efficiency and result quality that are usually considered when designing search interfaces. 1.