Gaze+touch vs. touch: what’s the trade-off when using gaze to extend touch to remote displays?

Direct touch input is employed on many devices, but it is inherently restricted to displays that are reachable by the user. Gaze input as a mediator can extend touch to remote displays - using gaze for remote selection, and touch for local manipulation - but at what cost and benefit? In this paper, we investigate the potential trade-off with four experiments that empirically compare remote Gaze+touch to standard touch. Our experiments investigate dragging, rotation, and scaling tasks. Results indicate that Gaze+touch is, compared to touch, (1) equally fast and more accurate for rotation and scaling, (2) slower and less accurate for dragging, and (3) enables selection of smaller targets. Our participants confirm this trend, and are positive about the relaxed finger placement of Gaze+touch. Our experiments provide detailed performance characteristics to consider for the design of Gaze+touch interaction of remote displays. We further discuss insights into strengths and drawbacks in contrast to direct touch

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

Embodied interaction with visualization and spatial navigation in time-sensitive scenarios

Paraphrasing the theory of embodied cognition, all aspects of our cognition are determined primarily by the contextual information and the means of physical interaction with data and information. In hybrid human-machine systems involving complex decision making, continuously maintaining a high level of attention while employing a deep understanding concerning the task performed as well as its context are essential. Utilizing embodied interaction to interact with machines has the potential to promote thinking and learning according to the theory of embodied cognition proposed by Lakoff. Additionally, the hybrid human-machine system utilizing natural and intuitive communication channels (e.g., gestures, speech, and body stances) should afford an array of cognitive benefits outstripping the more static forms of interaction (e.g., computer keyboard). This research proposes such a computational framework based on a Bayesian approach; this framework infers operator\u27s focus of attention based on the physical expressions of the operators. Specifically, this work aims to assess the effect of embodied interaction on attention during the solution of complex, time-sensitive, spatial navigational problems. Toward the goal of assessing the level of operator\u27s attention, we present a method linking the operator\u27s interaction utility, inference, and reasoning. The level of attention was inferred through networks coined Bayesian Attentional Networks (BANs). BANs are structures describing cause-effect relationships between operator\u27s attention, physical actions and decision-making. The proposed framework also generated a representative BAN, called the Consensus (Majority) Model (CMM); the CMM consists of an iteratively derived and agreed graph among candidate BANs obtained by experts and by the automatic learning process. Finally, the best combinations of interaction modalities and feedback were determined by the use of particular utility functions. This methodology was applied to a spatial navigational scenario; wherein, the operators interacted with dynamic images through a series of decision making processes. Real-world experiments were conducted to assess the framework\u27s ability to infer the operator\u27s levels of attention. Users were instructed to complete a series of spatial-navigational tasks using an assigned pairing of an interaction modality out of five categories (vision-based gesture, glove-based gesture, speech, feet, or body balance) and a feedback modality out of two (visual-based or auditory-based). Experimental results have confirmed that physical expressions are a determining factor in the quality of the solutions in a spatial navigational problem. Moreover, it was found that the combination of foot gestures with visual feedback resulted in the best task performance (p\u3c .001). Results have also shown that embodied interaction-based multimodal interface decreased execution errors that occurred in the cyber-physical scenarios (p \u3c .001). Therefore we conclude that appropriate use of interaction and feedback modalities allows the operators maintain their focus of attention, reduce errors, and enhance task performance in solving the decision making problems

An Overview of Self-Adaptive Technologies Within Virtual Reality Training

This overview presents the current state-of-the-art of self-adaptive technologies within virtual reality (VR) training. Virtual reality training and assessment is increasingly used for five key areas: medical, industrial & commercial training, serious games, rehabilitation and remote training such as Massive Open Online Courses (MOOCs). Adaptation can be applied to five core technologies of VR including haptic devices, stereo graphics, adaptive content, assessment and autonomous agents. Automation of VR training can contribute to automation of actual procedures including remote and robotic assisted surgery which reduces injury and improves accuracy of the procedure. Automated haptic interaction can enable tele-presence and virtual artefact tactile interaction from either remote or simulated environments. Automation, machine learning and data driven features play an important role in providing trainee-specific individual adaptive training content. Data from trainee assessment can form an input to autonomous systems for customised training and automated difficulty levels to match individual requirements. Self-adaptive technology has been developed previously within individual technologies of VR training. One of the conclusions of this research is that while it does not exist, an enhanced portable framework is needed and it would be beneficial to combine automation of core technologies, producing a reusable automation framework for VR training

Look together: using gaze for assisting co-located collaborative search

Gaze information provides indication of users focus which complements remote collaboration tasks, as distant users can see their partner’s focus. In this paper, we apply gaze for co-located collaboration, where users’ gaze locations are presented on the same display, to help collaboration between partners. We integrated various types of gaze indicators on the user interface of a collaborative search system, and we conducted two user studies to understand how gaze enhances coordination and communication between co-located users. Our results show that gaze indeed enhances co-located collaboration, but with a trade-off between visibility of gaze indicators and user distraction. Users acknowledged that seeing gaze indicators eases communication, because it let them be aware of their partner’s interests and attention. However, users can be reluctant to share their gaze information due to trust and privacy, as gaze potentially divulges their interests

A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion