Electrification is an important first step toward reducing the greenhouse emissions of passenger vehicles. However, how drivers drive, charge, and operate their electrified vehicles can have a large impact on their emissions, particularly for Plug-in Hybrid Electric vehicles (PHEVs) that combine all-electric driving with an internal combustion engine. In this paper, we investigate how and why drivers use their PHEVs and uncover design opportunities for interfaces that can support the efficient use of PHEVs. We used a mixed-method approach combining quantitative, qualitative, and concept elicitation methods with PHEV owners in the US. While past findings indicate that PHEV drivers are not motivated to charge regularly, our work contradicts this with evidence of (1) regular charging with home infrastructure, (2) high cost sensitivity, and (3) preference for driving in all-electric mode. Our results indicate that the most critical problem is inadequate user support for navigating poor charging infrastructure.

Videos are a convenient platform to begin, maintain, or improve a fitness program or physical activity. Traditional video systems allow users to manipulate videos through specific user interface actions such as button clicks or mouse drags, but have no model of what the user is doing and are unable to adapt in useful ways. We present adaptive video playback, which seamlessly synchronises video playback with the user's movements, building upon the principle of direct manipulation video navigation. We implement adaptive video playback in Reactive Video, a vision-based system which supports users learning or practising a physical skill. The use of pre-existing videos removes the need to create bespoke content or specially authored videos, and the system can provide real-time guidance and feedback to better support users when learning new movements. Adaptive video playback using a discrete Bayes and particle filter are evaluated on a data set collected of participants performing tai chi and radio exercises. Results show that both approaches can accurately adapt to the user's movements, however reversing playback can be problematic.

Work breaks--both physical and digital--play an important role in productivity and workplace wellbeing. Yet, the growing availability of digital distractions from online content can turn breaks into prolonged "cyberloafing". In this paper, we present UpTime, a system that aims to support workers' transitions from breaks back to work--moments susceptible to digital distractions. Combining a browser extension and chatbot, users interact with UpTime through proactive and reactive chat prompts. By sensing transitions from inactivity, UpTime helps workers avoid distractions by automatically blocking distracting websites temporarily, while still giving them control to take necessary digital breaks. We report findings from a 3-week comparative field study with 15 workers. Our results show that automatic, temporary blocking at transition points can significantly reduce digital distractions and stress without sacrificing workers' sense of control. Our findings, however, also emphasize that overloading users' existing communication channels for chatbot interaction should be done thoughtfully.

Responding to requests for information from an application, a remote person, or an organization that involve documenting the presence and/or state of physical objects can lead to incomplete or inaccurate documentation. We propose a system that couples information requests with a live object recognition tool to semi-automatically catalog requested items and collect evidence of their current state.

Despite work on smart spaces, nowadays a lot of knowledge work happens in the wild: at home, in coffee places, trains, buses, planes, and of course in crowded open office cubicles. Conducting web conferences in these settings creates privacy issues, and can also distract participants, leading to a perceived lack of professionalism from the remote peer(s). To solve this common problem, we implemented CamaLeon, a browser-based tool that uses real-time machine vision powered by deep learning to change the webcam stream sent by the remote peer. Specifically, CamaLeon dynamically changes the "wild" background into one that resembles that of the office workers. In order to detect the background in disparate settings, we designed and trained a fast UNet model on head and shoulder images. CamaLeon also uses a face detector to determine whether it should stream the person's face, depending on its location (or lack of presence). It uses face recognition to make sure it streams only a face that belongs to the user who connected to the meeting. We tested the system during a few real video conferencing calls at our company in which two workers are remote. Both parties felt a sense of enhanced co-presence, and the remote participants felt more professional with their background replaced.

In a telepresence scenario with remote users discussing a document, it can be difficult to follow which parts are being discussed. One way to address this is by showing the user's hand position on the document, which also enables expressive gestural communication. An important practical problem is how to capture and transmit the hand movements efficiently with high resolution document images. We propose a tabletop system with two channels that integrates document capture with a 4K video camera and hand tracking with a webcam, in which the document image and hand skeleton data are transmitted at different rates and handled by a lightweight Web browser client at remote sites. To enhance the rendering, we employ velocity based smoothing and ephemeral motion traces. We tested our prototype over long distances from USA to Japan and to Italy, and report on latency and jitter performance. Our system achieves relatively low latency over a long distance in comparison with a tele-immersive system that transmits mesh data over much shorter distances.

Historically, people have interacted with companies and institutions through telephone-based dialogue systems and paper-based forms. Now, these interactions are rapidly moving to web- and phone-based chat systems. While converting traditional telephone dialogues to chat is relatively straightforward, converting forms to conversational interfaces can be challenging. In this work, we introduce methods and interfaces to enable the conversion of PDF and web-based documents that solicit user input into chat-based dialogues. Document data is first extracted to associate fields and their textual descriptions using metadata and lightweight visual analysis. The field labels, their spatial layout, and associated text are further analyzed to group related fields into natural conversational units. These correspond to questions presented to users in chat interfaces to solicit information needed to complete the original documents and downstream processes they support. This user supplied data can be inserted into the source documents and/or in downstream databases. User studies of our tool show that it streamlines form-to-chat conversion and produces conversational dialogues of at least the same quality as a purely manual approach.

SlideDiff is a system that automatically creates an animated rendering of textual and media differences between two versions of a slide presentation. While previous work focused on either textual or image data, SlideDiff integrates both text and media changes, as well as their interactions, for example when adding an image forces nearby text boxes to shrink. Given two versions of a slide (not the full history of edits), SlideDiff detects the textual and image differences, and then animates the changes by mimicking what a user might have done, such as moving the cursor, typing text, resizing image boxes, adding images. This editing metaphor is well known to most users, helping them better understand what has changed, and fosters a sense of connection between remote workers, derived from communicating both the revision process as well as its results. After detection of text and image differences, the animations are rendered in HTML and CSS, including mouse cursor motion, text and image box selection and resizing, text deletion and insertion with its cursor. We discuss strategies for animating changes, in particular the importance of starting with large changes and finishing with smaller edits, and provide details of the implementation using modern HTML and CSS.

In this paper, we describe DocHandles, a novel system that allows users to link to specific document parts in their chat applications. As users type a message, they can invoke the tool by referring to a specific part of a document, e.g., "@fig1 needs revision". By combining text parsing and document layout analysis, DocHandles can find and present all the figures "1" inside previously shared documents, allowing users to explicitly link to the relevant "document handle". In this way, Ddocuments become first-class citizens inside the conversation stream where users can seamlessly integrate documents in their text-centric messaging application.

In this paper we describe DocuGram, a novel tool to capture and share documents originating from any application. As users scroll through pages of their document inside the native application (Word, Google Docs, web browser), the system captures and analyses in real-time the rendered video frames and reconstitutes the original document pages into an easy to view HTML-based representation. In addition to detecting and regenerating the document pages, a DocuGram also includes the interactions users had over them, e.g. mouse motions and voice comments. A DocuGram allows users to flexibly share enhanced documents across applications.

The proliferation of workplace multimedia collaboration applications has meant on one hand more opportunities for group work but on the other more data locked away in proprietary interfaces. We are developing new tools to capture and access multimedia content from any source. In this demo, we focus primarily on new methods that allow users to rapidly reconstitute, enhance, and share document-based information.

Live meeting documents require different techniques for effectively retrieving important pieces of information. During live meetings, people share web sites, edit presentation slides, and share code editors. A simple approach is to index with Optical Character Recognition (OCR) the video frames, or key-frames, being shared and let user retrieve them. Here we show that a more useful approach is to look at what actions users take inside the live document streams. Based on observations of real meetings, we focus on two important signals: text editing and mouse cursor motion. We describe the detection of text and cursor motion, their implementation in our WebRTC (Web Real-Time Communication)-based system, and how users are better able to search live documents during a meeting based on these extracted actions.

Establishing common ground is one of the key problems for any form of communication. The problem is particularly pronounced in remote meetings, in which participants can easily lose track of the details of dialogue for any number of reasons. In this demo we present a web-based tool, MixMeet, that allows teleconferencing participants to search the contents of live meetings so they can rapidly retrieve previously shared content to get on the same page, correct a misunderstanding, or discuss a new idea.

Distributed teams must co-ordinate a variety of tasks. To do so they need to be able to create, share, and annotate documents as well as discuss plans and goals. Many workflow tools support document sharing, while other tools support videoconferencing. However, there exists little support for connecting the two. In this work, we describe a system that allows users to share and markup content during web meetings. This shared content can provide important conversational props within the context of a meeting; it can also help users review archived meetings. Users can also extract content from meetings directly into their personal notes or other workflow tools.

Unlike text, copying and pasting parts of video documents is challenging. Yet, the abundance of video documents now available including how-to tutorials requires simpler tools that allow users to easily copy and paste fragments of video materials into new documents. We describe new direct video manipulation techniques enabling users to quickly copy and paste content from video documents into a user's own multimedia document. While the video plays, users interact with the video canvas to select text regions, scrollable regions, slide sequences built up across many frames, or semantically meaningful regions such as dialog boxes. Instead of relying on the timeline to accurately select sub-parts of the video document, users navigate using familiar selection techniques such as mouse-wheel to scroll back and forward over a video shot in which the content scrolls, double-clicks over rectangular regions to select them, or clicks and drags over textual regions of the video canvas to select them. We describe the video processing techniques that run in real-time in modern web browsers using HTML5 and JavaScript; and show how they help users quickly copy and paste video fragments into new documents, allowing them to efficiently reuse video documents for authoring or note-taking.

People frequently capture photos with their smartphones, and some are starting to capture images of documents. However, the quality of captured document images is often lower than expected, even when an application that performs post-processing to improve the image is used. To improve the quality of captured images before post-processing, we developed the Smart Document Capture (SmartDCap) application that provides real-time feedback to users about the likely quality of a captured image. The quality measures capture the sharpness and framing of a page or regions on a page, such as a set of one or more columns, a part of a column, a figure, or a table. Using our approach, while users adjust the camera position, the application automatically determines when to take a picture of a document to produce a good quality result. We performed a subjective evaluation comparing SmartDCap and the Android Ice Cream Sandwich (ICS) camera application; we also used raters to evaluate the quality of the captured images. Our results indicate that users find SmartDCap to be as easy to use as the standard ICS camera application. Also, images captured using SmartDCap are sharper and better framed on average than images using the ICS camera application.

We present a method for picture detection in document page images, which can come from scanned or camera images, or rendered from electronic file formats. Our method uses OCR to separate out the text and applies the Normalized Cuts algorithm to cluster the non-text pixels into picture regions. A refinement step uses the captions found in the OCR text to deduce how many pictures are in a picture region, thereby correcting for under- and over-segmentation. A performance evaluation scheme is applied which takes into account the detection quality and fragmentation quality. We benchmark our method against the ABBYY application on page images from conference papers.

Filling out document forms distributed by email or hosted on the Web is still problematic and usually requires a printer and scanner. Users commonly download and print forms, fill them out by hand, scan and email them. Even if the document is form-enabled (PDFs with FDF information), to read the file users still have to launch a separate application which may not be available, especially on mobile devices.

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 index is created from words on the presentation slides appearing in the video along with any associated metadata such as the title and abstract when available.

TalkMiner is a search engine for lecture webcasts. Lecture videos are processed to recover a set of distinct slide images and OCR is used to generate a list of indexable terms from the slides. On our prototype system, users can search and browse lists of lectures, slides in a specific lecture, and play the lecture video. Over 10,000 lecture videos have been indexed from a variety of sources. A public website will be published in mid 2010 that allows users to experiment with the search engine.

Most mobile navigation systems focus on answering the question, "I know where I want to go, now can you show me exactly how to get there?" While this approach works well for many tasks, it is not as useful for unconstrained situations in which user goals and spatial landscapes are more fluid, such as festivals or conferences. In this paper we describe the design and iteration of the Kartta system, which we developed to answer a slightly different question: "What are the most interesting areas here and how do I find them?"

PicNTell is a new technique for generating compelling screencasts where users can quickly record desktop activities and generate videos that are embeddable on popular video sharing distributions such as YouTube®. While standard video editing and screen capture tools are useful for some editing tasks, they have two main drawbacks: (1) they require users to import and organize media in a separate interface, and (2) they do not support natural (or camcorder-like) screen recording, and instead usually require the user to define a specific region or window to record. In this paper we review current screen recording use, and present the PicNTell system, pilot studies, and a new six degree-of-freedom tracker we are developing in response to our findings.

Plasma Posters are large screen, digital, interactive poster-boards situated in public spaces, designed to facilitate informal content sharing within teams, groups, organizations and communities. While interest i interactive community poster boards has grown recently, few successful examples have been reported. In this paper we describe an ongoing installation of Plasma Posters within our organization, and report qualitative and quantitative data from 20 months of use showing the Posters have become an integral part of information sharing, complementing email and Web-based sharing. Success factors include our design process, the reliability and flexibility of the technology and the social setting of our organization. We briefly describe three external installations of the Plasma Poster Network in public places. We then reflect on content posting as "information staging" and the ways in which the public space itself becomes part of the "interface" to content.

We introduce the AttrActive Windows user interface, a novel approach for presenting interactive content on large screen, interactive, digital, bulletin boards. Moving away from the desktop metaphor, AttrActive Windows are dynamic, non-uniform windows that can appear in different orientations and have autonomous behaviours to attract passers-by and invite interactions.

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Freeform digital ink annotation allows readers to interact with documents in an intuitive and familiar manner. Such marks are easy to manage on static documents, and provide a familiar annotation experience. In this paper, we describe an implementation of a freeform annotation system that accommodates dynamic document layout. The algorithm preserves the correct position of annotations when documents are viewed with different fonts or font sizes, with different aspect ratios, or on different devices. We explore a range of heuristics and algorithms required to handle common types of annotation, and conclude with a discussion of possible extensions to handle special kinds of annotations and changes to documents.