To combine the affordances of paper and computers, prior research has proposed numerous interactive paper systems that link specific paper document content to digital operations such as multimedia playback and proofreading. Yet, it remains unclear to what degree these systems bridge the inherent gap between paper and computers when compared to existing paper-only and computer-only interfaces. In particular, given the special properties of paper, such as limited dynamic feedback, how well does an average new user learn to master the interactive paper system? What factors affect the user performance? And how does the paper interface work in a typical use scenario? To answer these questions, we conducted two empirical experiments on a generic pen gesture based command system, called PapierCraft [Liao, et al., 2008], for paper-based interfaces. With it, people can select sections of printed document and issue commands such as copy and paste, linking and in-text search. The first experiment focused on the user performance of drawing pen gestures on paper. It proves that users can learn the command system in about 30 minutes and achieve a performance comparable to a Table PC-based interface supporting the same gestures. The second experiment examined the application of the command system in Active Reading tasks. The results show promise for seamless integration of paper and computers in Active Reading for their combined affordances. In addition, our study identifies some key design issues, such as the pen form factor and feedback of gestures. This paper contributes to better understanding on pros and cons of paper and computers, and sheds light on the design of future interfaces for document interaction.

Poster

The design and implementation of a search engine for lecture webcasts is described. A searchable text index is created allowing users to locate material within lecture videos found on a variety of websites such as YouTube and Berkeley webcasts. The searchable index is built from the text of presentation slides appearing in the video along with other associated metadata such as the title and abstract when available. The automatic identification of distinct slides within the video stream presents several challenges. For example, picture-in-picture compositing of a speaker and a presentation slide, switching cameras, and slide builds confuse basic algorithms for extracting keyframe slide images. Enhanced algorithms are described that improve slide identification. A public system was deployed to test the algorithms and the utility of the search engine at www.talkminer.com. To date, over 17,000 lecture videos have been indexed from a variety of public sources.

Modern office work practices increasingly breach traditional boundaries of time and place, making it difficult to interact with colleagues. To address these problems, we developed myUnity, a software and sensor platform that enables rich workplace awareness and coordination. myUnity is an integrated platform that collects information from a set of independent sensors and external data aggregators to report user location, availability, tasks, and communication channels. myUnity's sensing architecture is component-based, allowing channels of awareness information to be added, updated, or removed at any time. Multiple channels of input are combined and composited into a single, high-level presence state. Early studies of a myUnity deployment have demonstrated that the platform allows quick access to core awareness information and show that it has become a useful tool for supporting communication and collaboration in the modern workplace.

Presence systems are valuable in supporting workplace communication and collaboration. These systems are only effective if widely adopted and used. User perceptions of the utility of the information being shared and their comfort sharing such information strongly impact adoption and use. This paper describes the results of a survey of user preferences regarding comfort with and utility of workplace presence systems; the effects of sampling frequency, fidelity, and aggregation; and design implications of these results. We present new results that extend some past findings while challenging others. We contribute new design insights that inform the design of presence technologies to increase both utility and adoption.

Augmented Paper (AP) is an important area of Augmented Reality (AR). Many AP systems rely on visual features for paper doc-ument identification. Although promising, these systems can hardly support large sets of documents (i.e. one million documents) because of the high memory and time cost in handling high-dimensional features. On the other hand, general large-scale image identification techniques are not well customized to AP, costing unnecessarily more resource to achieve the identification accuracy required by AP. To address this mismatching between AP and image identification techniques, we propose a novel large-scale image identification technique well geared to AP. At its core is a geometric verification scheme based on Minimum visual-word Correspondence Set (MICSs). MICS is a set of visual word (i.e. quantized visual fea-ture) correspondences, each of which contains a minimum number of correspondences that are sufficient for deriving a transformation hypothesis between a captured document image and an indexed image. Our method selects appropriate MICSs to vote in a Hough space of transformation parameters, and uses a robust dense region detection algorithm to locate the possible transformation models in the space. The models are then utilized to verify all the visual word correspondence to precisely identify the matching indexed image. By taking advantage of unique geometric constraints in AP, our method can significantly reduce the time and memory cost while achieving high accuracy. As showed in evaluation with two AP systems called FACT and EMM, over a dataset with 1M+ images, our method achieves 100% identification accuracy and 0.67% registration error for FACT; For EMM, our method outperforms the state-of-the-art image identification approach by achieving 4% improvements in detection rate and almost perfect precision, while saving 40% and 70% memory and time cost.

PaperUI is a human-information interface concept that advocates using paper as displays and using mobile devices, such as camera phones or camera pens, as traditional computer-mice. When emphasizing technical efforts, some researchers like to refer the PaperUI related underlying work as interactive paper system. We prefer the term PaperUI for emphasizing the final goal, narrowing the discussion focus, and avoiding terminology confusion between interactive paper system and interactive paper computer [40]. PaperUI combines the merits of paper and the mobile devices, in that users can comfortably read and flexibly arrange document content on paper, and access digital functions related to the document via the mobile computing devices. This concept aims at novel interface technology to seamlessly bridge the gap between paper and computers for better user experience in handling documents. Compared with traditional laptops and tablet PCs, devices involved in the PaperUI concept are more light-weight, compact, energy efficient, and widely adopted. Therefore, we believe this interface vision can make computation more convenient to access for general public.

This paper describes methods for clustering photos that include both time stamps and location coordinates. We present versions of a two part method that first detects clusters using time and location information independently. These candidate clusters partition the set of time-ordered photos. A subset of the candidate clusters is selected by an efficient dynamic programming procedure to optimize a cost function. We propose several cost functions to design clusterings that are coherent in space, time, or both. One set of cost functions minimizes inter-photo distances directly. A second set maximizes an information measure to select clusterings for consistency in both time and space across scale.

Embedded Media Markers (EMMs) are nearly transparent icons printed on paper documents that link to associated digital media. By using the document content for retrieval, EMMs are less visually intrusive than barcodes and other glyphs while still providing an indication for the presence of links. An initial implementation demonstrated good overall performance but exposed difficulties in guaranteeing the creation of unambiguous EMMs. We developed an EMM authoring tool that supports the interactive authoring of EMMs via visualizations that show the user which areas on a page may cause recognition errors and automatic feedback that moves the authored EMM away from those areas. The authoring tool and the techniques it relies on have been applied to corpora with different visual characteristics to explore the generality of our approach.

The Active Reading Application (ARA) brings the familiar experience of writing on paper to the tablet. The application augments paper-based practices with audio, the ability to review annotations, and sharing. It is designed to make it easier to review, annotate, and comment on documents by individuals and groups. ARA incorporates several patented technologies and draws on several years of research and experimentation.

Modern office work practices increasingly breach traditional boundaries of time and place, making it difficult to interact with colleagues. To address these problems, we developed myUnity, a software and sensor platform that enables rich workplace awareness and coordination. myUnity is an integrated platform that collects information from a set of independent sensors and external data aggregators to report user location, availability, tasks, and communication channels. myUnity's sensing architecture is component-based, allowing channels of awareness information to be added, updated, or removed at any time. Our current system includes a variety of sensor and data input, including camera-based activity classification, wireless location trilateration, and network activity monitoring. These and other input channels are combined and composited into a single, high-level presence state. Early studies of a myUnity deployment have demonstrated that use of the platform allows quick access to core awareness information and show it has become a useful tool supporting communication and collaboration in the modern workplace.

We illustrate the use of Querium, a novel search system designed to support people's collaborative and multi-session search tasks, in the context of the HCIR 2011 Search Challenge. This report demonstrates how a Querium's interface and search engine can be used to search for documents in an open-ended, exploratory task. We illustrate the use of relevance feedback, faceted search, query fusion, and the search history, as well as commenting and overview functions.

Information seeking is often a collaborative activity that can take can take many forms; in this paper we focus on explicit, intentional collaboration of small and explore a range of design decisions that should be considered when building Human-Computer Information Retrieval (HCIR) tools that support collaboration. In particular, we are interested in exploring the interplay between algorithmic mediation of collaboration and the mediated communication among team members. We argue that certain characteristics of the group's information need call for different design decisions.

Documents created, stored, and retrieved digitally are often printed on paper to be read for the purposes of producing new documents. The cycle of electronic document "consumption" and production is often broken in the middle by printing. Our research in XLibris has examined these transitions between the digital and paper worlds. Starting with interfaces for analytic reading, we have focused on annotation, on retrieval and re-retrieval, and on shared annotation. In this talk, I will describe the interfaces and the empirical evaluations we have conducted, and will discuss the potential of this technology in digital--and in physical--libraries.

PaperUI is a human-computer interface concept that treats paper as displays that users can interact with via mobile devices such as mobile phones and projectors. It combines the merits of paper and the mobile devices. Compared with traditional laptops and tablet PCs, devices involved in this concept are more light-weight, compact, energy efficient, and widely adopted. Therefore, we believe this interface vision can make computation more convenient to access for general public. With our implemented prototype, pilot users can read documents easily and comfortably on paper, and access many digital functions related to the document via a camera phone or a mobile projector Invited Talk. http://imlab.jp/cbdar2011/#keynote

This demo shows an interactive paper system called MixPad, which features using mice and keyboards to enhance the conventional pen-finger-gesture based interaction with paper documents. Similar to many interactive paper systems, MixPad adopts a mobile camera-projector unit to recognize paper documents, detect pen and finger gestures and provide visual feedback. Unlike these systems, MixPad allows using mice and keyboards to help users interact with fine-grained document content on paper (e.g. individual words and user-defined arbitrary regions), and to facilitate cross-media operations. For instance, to copy a document segment from paper to a laptop, one first points a finger of her non-dominant hand to the segment roughly, and then uses a mouse in her dominant hand to refine the selection and drag it to the laptop; she can also type text as a detailed comment on a paper document. This novel interaction paradigm combines the advantages of mice, keyboards, pens and fingers, and therefore enables rich digital functions on paper.

Modern office work practices increasingly breach traditional boundaries of time and place, increasing breakdowns workers encounter when coordinating interaction with colleagues. We conducted interviews with 12 workers and identified key problems introduced by these practices. To address these problems we developed myUnity, a fully functional platform enabling rich workplace awareness and coordination. myUnity is one of the first integrated platforms to span mobile and desktop environments, both in terms of access and sensing. It uses multiple sources to report user location, availability, tasks, and communication channels. A pilot field study of myUnity demonstrated the significant value of pervasive access to workplace awareness and communication facilities, as well as positive behavioral change in day-to-day communication practices for most users. We present resulting insights about the utility of awareness technology in flexible work environments.

Mobile media applications need to balance user and group goals, attentional constraints, and limited screen real estate. In this paper, we describe the iterative development and testing of an application that explores these tradeoffs. We developed early prototypes of a retrospective, time-based system as well as a prospective and space-based system. Our experiences with the prototypes led us to focus on the prospective system. We argue that attentional demands dominate and mobile media applications should be lightweight and hands-free as much as possible.

Temporal aspects of documents can impact relevance for certain kinds of queries. In this paper, we build on earlier work of modeling temporal information. We propose an extension to the Query Likelihood Model that incorporates query-specific information to estimate rate parameters, and we introduce a temporal factor into language model smoothing and query expansion using pseudo-relevance feedback. We evaluate these extensions using a Twitter corpus and two newspaper article collections. Results suggest that, compared to prior approaches, our models are more effective at capturing the temporal variability of relevance associated with some topics.

As sensors become ever more prevalent, more and more information will be collected about each of us. A longterm research question is how best to support beneficial uses while preserving individual privacy. Presence systems are an emerging class of applications that support collaboration. These systems leverage pervasive sensors to estimate end-user location, activities, and available communication channels. Because such presence data are sensitive, to achieve wide-spread adoption, sharing models must reflect the privacy and sharing preferences of the users. To reflect users' collaborative relationships and sharing desires, we introduce CollaPSE security in which an individual has full access to her own data, a third party processes the data without learning anything about the data values, and users higher up in the hierarchy learn only statistical information about the employees under them. We describe simple schemes that efficiently realize CollaPSE security for time series data. We implemented these protocols using readily available cryptographic functions, and integrated the protocols with FXPAL's MyUnity presence system.

The field of personal mobile projection is advancing quickly and a variety of work focuses on enhancing physical objects in the real world with dynamically projected digital artifacts. Due to technological restrictions, none of them has yet investigated, what we feel is the most promising research direction: the (bi-manual) interaction with mobile projections on non-planar surfaces. To elicit the challenges of this field of research, we contribute (1) a technology-centered design space for mobile projector-based interfaces and discus related work in light thereof, (2) a discussion on lessons learnt from two of our research projects, which aim at improving both usability and user experience and (3) an outline of open research challenges within this field.

For document visualization, folding techniques provide a focus-plus-context approach with fairly high legibility on flat sections. To enable richer interaction, we explore the design space of multi-touch document folding. We discuss several design considerations for simple modeless gesturing and compatibility with standard Drag and Pinch gestures, and categorize gesture models along the characteristics of Symmetric/Asymmetric and Sequential/Parallel, which yields three gesture models. We built a prototype document workspace application that integrates folding and standard gestures, and a prototype for experimenting with the gesture models. A user study was conducted to compare the three models and to analyze the factors of fold direction, target symmetry, and target tolerance in user performance of folding a document to a specific shape. Our results indicate that all three factors were significant for task times, and parallelism was greater for symmetric targets.

A variety of applications are emerging to support streaming video from mobile devices. However, many tasks can benefit from streaming specific content rather than the full video feed which may include irrelevant, private, or distracting content. We describe a system that allows users to capture and stream targeted video content captured with a mobile device. The application incorporates a variety of automatic and interactive techniques to identify and segment desired content, allowing the user to publish a more focused video stream.

User-generated video from mobile phones, digital cameras, and other devices is increasing, yet people rarely want to watch all the captured video. More commonly, users want a single still image for printing or a short clip from the video for creating a panorama or for sharing. Our interface aims to help users search through video for these images or clips in a more efficient fashion than fast-forwarding or "scrubbing" through a video by dragging through locations on a slider. It is based on a hierarchical structure of keyframes in the video, and combines a novel user interface design for browsing a video segment tree with new algorithms for keyframe selection, segment identification, and clustering. These algorithms take into account the need for quality keyframes and balance the desire for short navigation paths and similarity-based clusters. Our user interface presents keyframe hierarchies and displays visual cues for keeping the user oriented while browsing the video. The system adapts to the task by using a non-temporal clustering algorithm when a the user wants a single image. When the user wants a video clip, the system selects one of two temporal clustering algorithm based on a measure of the repetitiveness of the video. User feedback provided us with valuable suggestions for improvements to our system.

Embedded Media Marker (EMM) identification system allows users to retrieve relevant dynamic media associated with a static paper document via camera phones. The user supplies a query image by capturing an EMM-signified patch of a paper document through a camera phone; the system recognizes the query and in turn retrieves and plays the corresponding media on the phone. Accurate image matching is crucial for positive user experience in this application. To address the challenges posed by large datasets and variations in camera-phone-captured query images, we introduce a novel image matching scheme based on geometrically consistent correspondences. Two matching constraints - "injection" and "approximate global geometric consistency" (AGGC), which are unique in EMM identification, are presented. A hierarchical scheme, combined with two constraining functions, is designed to detect the "injective-AGGC" correspondences between images. A spatial neighborhood search approach is further proposed to address challenging cases with large translational shift. Experimental results on a 100k+ dataset show that our solution achieves high accuracy with low memory and time complexity and outperforms the standard bag-of-words approach.