Stacie Lynn Hibino

handiMessenger: Awareness-Enhanced Universal Communication for Mobile Users

Successfully contacting colleagues while away from the office is especially difficult without information about their availability and location. HandiMessenger is a service designed to facilitate opportunistic communication by tightly integrating awareness and contact capabilities into a wireless, unified messaging and awareness application. Users can securely access intranet email, instant messages, and other messages from a handheld mobile device (e.g., a wireless PDA). Simultaneously, they are presented with awareness information about the sender to enable a reply in the most appropriate mode, given the situation of the participants. For example, they can read email and reply by initiating a phone call, if the sender is available by phone. Analysis of handiMessenger usage shows that users do request awareness information while inspecting message headers or content, and that users also, at times, respond to a message with a different type or in a different mode than the original message.

Reminiscing View: Event-Based Browsing of Consumer's Photo and Video-Clip Collections

The Reminiscing View is a visualization system for browsing hierarchically organized photo and video-clip collections. The current Reminiscing View prototype supports browsing of hierarchical temporal event clusters. Users simply upload their pictures and video clips to a server and their collection is automatically clustered into hierarchical temporal events. They can then browse events in a chronologically ordered spiral or grid view and explore details of each event. They can also filter the displayed media by date, text-based search, and sharing group. The addition of a remote control interface to the system allows users to browse their collection in a ldquolean backrdquo setting such as a living room environment. This paper describes the system and interface of the Reminiscing View. It also presents results and implications of a user study conducted on an earlier version of the system.

Searching consumer image collections using web-based concept expansion

As consumers accumulate more and more personal imagery, searching for specific images has become increasingly difficult. Consumers typically provide little or no annotations, and automated classifiers and concept tagging tools are limited in their scope and vocabulary. This work addresses this sparsity of semantic information by leveraging domain-specific information provided by online photo-sharing communities. Such information enables improved search by allowing user-provided search terms to be expanded into a set of semantically related concepts, using relevant semantic relationships provided by millions of users. Our system first extracts metadata using a modest number of image and event-based semantic classifiers, as well as any meaningful file or folder names. When users pose text-based queries, our system retrieves images from their personal image collections by leveraging Flickrs tag dataset for concept expansion. This approach enables users to search their collections without having to manually annotate their pictures. We compare the retrieval performance of using a Flickr-based concept expander with the performance obtained without concept expansion and with using a WordNet-based concept expander. The results demonstrate that common sense knowledge gleaned from online photo sharing communities can enable meaningful image search on consumer image collections, searches that would be impossible using only the available image metadata.

Event-centric View of Consumer Image Collections

Benchmark and ground truth databases are critical for evaluating imaging- and event-based algorithms, but such databases can be time consuming to create, cannot be representative of all real-life consumer image collections, and do not necessarily provide feedback on the general utility of an imperfect algorithm applied to real-life data. An alternative solution is needed to complement evaluation by benchmark and ground truth databases. We designed and developed Event Analyzer as a tool to meet this need. Event Analyzer combines data visualization of metadata with event and image retrieval results in a way that enables researchers to easily review data trends, quickly filter and select data, see relationships between metadata values, and visually scan retrieved results to determine correctness. In this paper, we describe the tool and discuss how it can and has been used to analyze real-life consumer collections in an event-centric manner.

Semantics Meets UX: Mediating Intelligent Indexing of Consumers' Multimedia Collections for Multifaceted Visualization and Media Creation

Unorganized media collections hinder consumers from fully experiencing and enjoying their visual media. User interfaces can mediate the results of automated indexing by presenting data and interactions that leverage the strengths of individual and combined algorithm results, supporting multifaceted browsing, and enabling user correction in a way that is not disruptive to the userspsila activities. We describe the semantic system demonstration framework (SSDF), a flexible and extensible framework for combining multiple semantic indexing algorithms for consumer photo and video clip collections into one integrated system. We also describe key features of Koi, an SSDF desktop client application with a user interface designed to mediate and leverage the intelligent indexing incorporated in the SSDF server. Together, Koi and SSDF empower users to experience their personal multimedia in novel and sophisticated ways.