Destination maps are navigational aids designed to show anyone within a region how to reach a location (the destination). Hand-designed destination maps include only the most important roads in the region and are non-uniformly scaled to ensure that all of the important roads from the highways to the residential streets are visible. We present the first automated system for creating such destination maps based on the design principles used by mapmakers. Our system includes novel algorithms for selecting the important roads based on mental representations of road networks, and for laying out the roads based on a non-linear optimization procedure. The final layouts are labeled and rendered in a variety of styles ranging from informal to more formal map styles. The system has been used to generate over 57,000 destination maps by thousands of users. We report feedback from both a formal and informal user study, as well as provide quantitative measures of success.

We present a promising new framework for improving boosting performance with transductive inference when training an automatic text detector. The resulting detector is fast and efficient, and it exhibits high accuracy on a large test set.

This paper describes an approach for locating annotations generated in one video and properly placing them in a second, modified version of the same video. We focus on modifications that standard Television (TV) broadcasts may experience, including content insertion and deletion (i.e., commercials), format conversions and different start/end recording times. To overcome these modifications, we propose content-based video timelines. We identify the position of a frame in a long video stream with an accuracy of one frame based on its content, without using embedded time codes. To make this approach feasible, we use a compact representation of a video frame, which we call a "fingerprint". Fingerprints capture small temporal variations within shots and therefore allow precise position recovery. Our fingerprints' efficient storage size, extraction time and comparison complexity suggest that our approach can be applied using off-the-shelf PCs and TV "set-top" boxes.

Annotating paper documents with a pen is a familiar and indispensable activity across a wide variety of work and educational settings. Recent developments in pen-based computing promise to bring this experience to digital documents. However, digital documents are more flexible than their paper counterparts. When a digital document is edited, or displayed on different devices, its layout adapts to the new situation. Freeform digital ink annotations made on such a document must likewise adapt, or "reflow." But their unconstrained nature yields only vague guidelines for how these annotations should be transformed. Few systems have considered this issue, and still fewer have addressed it from a user's point of view. This paper reports the results of a study of user expectations for reflowing digital ink annotations. We explore user reaction to reflow in common cases, how sensitive users are to reflow errors, and how important it is that personal style survive reflow. Our findings can help designers and system builders support freeform annotation more effectively.

Grid-based page designs are ubiquitous in commercially printed publications, such as newspapers and magazines. Yet, to date, no one has invented a good way to easily and automatically adapt such designs to arbitrarily-sized electronic displays. The difficulty of generalizing grid-based designs explains the generally inferior nature of on-screen layouts when compared to their printed counterparts, and is arguably one of the greatest remaining impediments to creating on-line reading experiences that rival those of ink on paper. In this work, we present a new approach to adaptive grid-based document layout, which attempts to bridge this gap. In our approach, an adaptive layout style is encoded as a set of grid-based templates that know how to adapt to a range of page sizes and other viewing conditions. These templates include various types of layout elements (such as text, figures, etc.) and define, through constraint-based relationships, just how these elements are to be laid out together as a function of both the properties of the content itself, such as a figure's size and aspect ratio, and the properties of the viewing conditions under which the content is being displayed. We describe an XML-based representation for our templates and content, which maintains a clean separation between the two. We also describe the various parts of our research prototype system: a layout engine for formatting the page; a paginator for determining a globally optimal allocation of content amongst the pages, as well as an optimal pairing of templates with content; and a graphical user interface for interactively creating adaptive templates. We also provide numerous examples demonstrating the capabilities of this prototype, including this paper, itself, which has been laid out with our system.

Notification and shared annotations go hand-in-hand. Notification of activity in a shared document system is known to support awareness and improve asynchronous collaboration, but few studies have examined user needs and explored design tradeoffs. We examined large-scale use of notifications in a commercial system and found it lacking. We designed and deployed enhancements to the system, then conducted a field study to gauge their effect. We found that providing more information in notification messages, supporting multiple communication channels through which notifications can be received, and allowing customization of notification messages are particularly important. Overall awareness of annotation activity on software specifications increased with our enhancements

Increasingly, documents exist primarily in digital form. System designers have recently focused on making it easier to read digital documents, with annotation as an important new feature. But supporting annotation well is difficult because digital documents are frequently modified, making it challenging to correctly reposition annotations in modified versions. Few systems have addressed this issue, and even fewer have approached the problem from the users' point of view. This paper reports the results of two studies examining user expectations for robust annotation positioning in modified documents. We explore how users react to lost annotations, the relationship between types of document modifications and user expectations, and whether users pay attention to text surrounding their annotations. Our results could contribute substantially to effective digital document annotation systems.