Space for Two to Think: Large, High-Resolution Displays for Co-located Collaborative Sensemaking

Large, high-resolution displays carry the potential to enhance single display groupware collaborative sensemaking for intelligence analysis tasks by providing space for common ground to develop, but it is up to the visual analytics tools to utilize this space effectively. In an exploratory study, we compared two tools (Jigsaw and a document viewer), which were adapted to support multiple input devices, to observe how the large display space was used in establishing and maintaining common ground during an intelligence analysis scenario using 50 textual documents. We discuss the spatial strategies employed by the pairs of participants, which were largely dependent on tool type (data-centric or function-centric), as well as how different visual analytics tools used collaboratively on large, high-resolution displays impact common ground in both process and solution. Using these findings, we suggest design considerations to enable future co-located collaborative sensemaking tools to take advantage of the benefits of collaborating on large, high-resolution displays

Large High Resolution Displays for Co-Located Collaborative Intelligence Analysis

Large, high-resolution vertical displays carry the potential to increase the accuracy of collaborative sensemaking, given correctly designed visual analytics tools. From an exploratory user study using a fictional intelligence analysis task, we investigated how users interact with the display to construct spatial schemas and externalize information, as well as how they establish shared and private territories. We investigated the spatial strategies of users partitioned by tool type used (document- or entity-centric). We classified the types of territorial behavior exhibited in terms of how the users interacted with the display (integrated or independent workspaces). Next, we examined how territorial behavior impacted the common ground between the pairs of users. Finally, we recommend design guidelines for building co-located collaborative visual analytics tools specifically for use on large, high-resolution vertical displays

A Comparison of Visualisation Methods for Disambiguating Verbal Requests in Human-Robot Interaction

Picking up objects requested by a human user is a common task in human-robot interaction. When multiple objects match the user's verbal description, the robot needs to clarify which object the user is referring to before executing the action. Previous research has focused on perceiving user's multimodal behaviour to complement verbal commands or minimising the number of follow up questions to reduce task time. In this paper, we propose a system for reference disambiguation based on visualisation and compare three methods to disambiguate natural language instructions. In a controlled experiment with a YuMi robot, we investigated real-time augmentations of the workspace in three conditions -- mixed reality, augmented reality, and a monitor as the baseline -- using objective measures such as time and accuracy, and subjective measures like engagement, immersion, and display interference. Significant differences were found in accuracy and engagement between the conditions, but no differences were found in task time. Despite the higher error rates in the mixed reality condition, participants found that modality more engaging than the other two, but overall showed preference for the augmented reality condition over the monitor and mixed reality conditions

Literature Survey on Interaction Techniques for Large Displays

When designing for large screen displays, designers are forced to deal with cursor tracking issues, interacting over distances, and space management issues. Because of the large visual angle of the user that the screen can cover, it may be hard for users to begin and complete search tasks for basic items such as cursors or icons. In addition, maneuvering over long distances and acquiring small targets understandably takes more time than the same interactions on normally sized screen systems. To deal with these issues, large display researchers have developed more and more unconventional devices, methods and widgets for interaction, and systems for space and task management. For tracking cursors there are techniques that deal with the size and shape of the cursor, as well as the “density” of the cursor. There are other techniques that help direct the attention of the user to the cursor. For target acquisition on large screens, many researchers saw fit to try to augment existing 2D GUI metaphors. They try to optimize Fitts’ law to accomplish this. Some techniques sought to enlarge targets while others sought to enlarge the cursor itself. Even other techniques developed ways of closing the distances on large screen displays. However, many researchers feel that existing 2D metaphors do not and will not work for large screens. They feel that the community should move to more unconventional devices and metaphors. These unconventional means include use of eye-tracking, laser-pointing, hand-tracking, two-handed touchscreen techniques, and other high-DOF devices. In the end, many of these developed techniques do provide effective means for interaction on large displays. However, we need to quantify the benefits of these methods and understand them better. The more we understand the advantages and disadvantages of these techniques, the easier it will be to employ them in working large screen systems. We also need to put into place a kind of interaction standard for these large screen systems. This could mean simply supporting desktop events such as pointing and clicking. It may also mean that we need to identify the needs of each domain that large screens are used for and tailor the interaction techniques for the domain

Designing to Support Workspace Awareness in Remote Collaboration using 2D Interactive Surfaces

Increasing distributions of the global workforce are leading to collaborative workamong remote coworkers. The emergence of such remote collaborations is essentiallysupported by technology advancements of screen-based devices ranging from tabletor laptop to large displays. However, these devices, especially personal and mobilecomputers, still suffer from certain limitations caused by their form factors, that hinder supporting workspace awareness through non-verbal communication suchas bodily gestures or gaze. This thesis thus aims to design novel interfaces andinteraction techniques to improve remote coworkers’ workspace awareness throughsuch non-verbal cues using 2D interactive surfaces.The thesis starts off by exploring how visual cues support workspace awareness infacilitated brainstorming of hybrid teams of co-located and remote coworkers. Basedon insights from this exploration, the thesis introduces three interfaces for mobiledevices that help users maintain and convey their workspace awareness with their coworkers. The first interface is a virtual environment that allows a remote person to effectively maintain his/her awareness of his/her co-located collaborators’ activities while interacting with the shared workspace. To help a person better express his/her hand gestures in remote collaboration using a mobile device, the second interfacepresents a lightweight add-on for capturing hand images on and above the device’sscreen; and overlaying them on collaborators’ device to improve their workspace awareness. The third interface strategically leverages the entire screen space of aconventional laptop to better convey a remote person’s gaze to his/her co-locatedcollaborators. Building on the top of these three interfaces, the thesis envisions an interface that supports a person using a mobile device to effectively collaborate with remote coworkers working with a large display.Together, these interfaces demonstrate the possibilities to innovate on commodity devices to offer richer non-verbal communication and better support workspace awareness in remote collaboration

Behavioral patterns of individuals and groups during co-located collaboration on large, high-resolution displays

Collaboration among multiple users on large screens leads to complicated behavior patterns and group dynamics. To gain a deeper understanding of collaboration on vertical, large, high-resolution screens, this dissertation builds on previous research and gains novel insights through new observational studies. Among other things, the collected results reveal new patterns of collaborative coupling, suggest that territorial behavior is less critical than shown in previous research, and demonstrate that workspace awareness can also negatively affect the effectiveness of individual users

"Not the Usual Suspects": A Study of Factors Reducing the Effectiveness of CCTV

Previous research on the effectiveness of Closed Circuit Television (CCTV) has focused on critically assessing police and government claims that CCTV is effective in reducing crime. This paper presents a field study that investigates the relationship between CCTV system design and the performance of operator tasks. We carried out structured observations and interviews with 13 managers and 38 operators at 13 CCTV control rooms. A number of failures were identified, including the poor configuration of technology, poor quality video recordings, and a lack of system integration. Stakeholder communication was poor, and there were too many cameras and too few operators. These failures have been previously identified by researchers; however, no design improvements have been made to control rooms in the last decade. We identify a number of measures to improve operator performance, and contribute a set of recommendations for security managers and practitioners. Security Journal (2010) 23, 134-154. doi:10.1057/sj.2008.2; published online 6 October 200