Next-Generation text entry

Users are reluctant to learn new text entry methods, as they demand a substantial training investment. Allowing users to flexibly combine multiple existing probabilistic text entry modalities is a way to still provide performance benefits to users.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/MC.2015.18

Inattention-Management Middleware for Human-in-the-Loop Multi-Display Applications

Operator inattention is an important and unsolved problem in mission critical multi-display systems where a single or a group of operators continuously monitor information flows on distributed displays. In this paper we present a novel system solution to this problem and a middleware for supporting flexible attention-aware applications for a variety of domains. Some of the most significant functionality includes direct querying of the application’s attention state, custom callback definitions to be executed on specific attention events or application updates, inter-application message routing, and pushing custom notification with relative location information to any other registered application. We evaluate our middleware by developing three applications that both demonstrate the efficacy and versatility of the system and provide performance estimates in terms of latency as a function of payload size

Mining, analyzing, and modeling text written on mobile devices

AbstractWe present a method for mining the web for text entered on mobile devices. Using searching, crawling, and parsing techniques, we locate text that can be reliably identified as originating from 300 mobile devices. This includes 341,000 sentences written on iPhones alone. Our data enables a richer understanding of how users type “in the wild” on their mobile devices. We compare text and error characteristics of different device types, such as touchscreen phones, phones with physical keyboards, and tablet computers. Using our mined data, we train language models and evaluate these models on mobile test data. A mixture model trained on our mined data, Twitter, blog, and forum data predicts mobile text better than baseline models. Using phone and smartwatch typing data from 135 users, we demonstrate our models improve the recognition accuracy and word predictions of a state-of-the-art touchscreen virtual keyboard decoder. Finally, we make our language models and mined dataset available to other researchers.</jats:p

A Conceptual Design of an Inattention Management Middleware with Adaptive Target Saliency

© 2020 IEEE. We present a conceptual design of an inattention management middleware with adaptive target saliency. The design objective is to provide mechanisms for managing operator inattention in multi-display multitasking applications. The conceptual design integrates ideas from situational awareness into its mechanisms to provide dynamic target saliency as a means to 1) guide operators through sub-tasks by drawing attention to high priority targets; and 2) guide operators on how to efficiently split their attention between tasks. We motivate the design by analysis of the results following a formative study with a prototype version of the conceptual design

An evaluation of discrete and continuous mid-air loop and marking menu selection in optical see-through HMDs

© 2019 Copyright held by the owner/author(s). This paper investigates discrete and continuous hand-drawn loops and marks in mid-air as a selection input for gesture-based menu systemsonoptical see-through head-mounteddisplays (OST HMDs). We explore two fundamental methods of providing menu selection: the marking menu and the loop menu, and a hybrid method which combines the two. The loop menu design uses a selection mechanism with loops to approximate directional selections in a menu system. We evaluate the merits of loop and marking menu selection in an experiment with two phases and report that 1) the loop-based selection mechanism provides smooth and effective interaction; 2) users prioritize accuracy and comfort over speed for mid-air gestures; 3) users can exploit the flexibility of a final hybrid marking/loop menu design; and, finally, 4) users tend to chunk gestures depending on the selection task and their level of familiarity with the menu layout

Differentiation of online text-based advertising and the effect on users' click behavior

Online syndicated text-based advertising is ubiquitous on news sites, blogs, personal websites, and on search result pages. Until recently, a common distinguishing feature of these text-based advertisements has been their background color. Following intervention by the Federal Trade Commission (FTC), the format of these advertisements has undergone a subtle change in their design and presentation. Using three empirical experiments, we investigate the effect of industry-standard advertising practices on click rates, and demonstrate changes in user behavior when this familiar differentiator is modified. Using three large-scale experiments (N1 = 101, N2 = 84, N3 = 176) we find that displaying advertisement and content results with a differentiated background results in significantly lower click rates. Our results demonstrate the strong link between background color differentiation and advertising, and reveal how alternative differentiation techniques influence user behavior.This work was supported by a studentship from the Engineering and Physical Sciences Research Council.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0747563215003180#. Additional data related to this publication is available at the University of Cambridge data repository: http://www.repository.cam.ac.uk/handle/1810/247391

Crowdsourcing interface feature design with Bayesian optimization

Designing novel interfaces is challenging. Designers typically rely on experience or subjective judgment in the absence of analytical or objective means for selecting interface parameters. We demonstrate Bayesian optimization as an efficient tool for objective interface feature refinement. Specifically, we show that crowdsourcing paired with Bayesian optimization can rapidly and effectively assist interface design across diverse deployment environments. Experiment 1 evaluates the approach on a familiar 2D interface design problem: a map search and review use case. Adding a degree of complexity, Experiment 2 extends Experiment 1 by switching the deployment environment to mobile-based virtual reality. The approach is then demonstrated as a case study for a fundamentally new and unfamiliar interaction design problem: web-based augmented reality. Finally, we show how the model generated as an outcome of the refinement process can be used for user simulation and queried to deliver various design insights

Change Blindness in Proximity-Aware Mobile Interfaces

Interface designs on both small and large displays can encourage people to alter their physical distance to the display. Mobile devices support this form of interaction naturally, as the user can move the device closer or further away as needed. The current generation of mobile devices can employ computer vision, depth sensing and other inference methods to determine the distance between the user and the display. Once this distance is known, a system can adapt the rendering of display content accordingly and enable proximity-aware mobile interfaces. The dominant method of exploiting proximity-aware interfaces is to remove or superimpose visual information. In this paper, we investigate change blindness in such interfaces. We present the results of two experiments. In our first experiment we show that a proximity-aware mobile interface results in significantly more change blindness errors than a non-moving interface. The absolute difference in error rates was 13.7%. In our second experiment we show that within a proximity-aware mobile interface, gradual changes induce significantly more change blindness errors than instant changes— confirming expected change blindness behavior. Based on our results we discuss the implications of either exploiting change blindness effects or mitigating them when designing mobile proximity-aware interfaces

AeroVR: An immersive visualisation system for aerospace design and digital twinning in virtual reality

ABSTRACTOne of today’s most propitious immersive technologies is virtual reality (VR). This term is colloquially associated with headsets that transport users to a bespoke, built-for-purpose immersive 3D virtual environment. It has given rise to the field of immersive analytics—a new field of research that aims to use immersive technologies for enhancing and empowering data analytics. However, in developing such a new set of tools, one has to ask whether the move from standard hardware setup to a fully immersive 3D environment is justified—both in terms of efficiency and development costs. To this end, in this paper, we present AeroVR—an immersive aerospace design environment with the objective of aiding the component aerodynamic design process by interactively visualizing performance and geometry. We decompose the design of such an environment into function structures, identify the primary and secondary tasks, present an implementation of the system, and verify the interface in terms of usability and expressiveness. We deploy AeroVR on a prototypical design study of a compressor blade for an engine.This work was supported by studentships from the Engineering and Physical Sciences Research Council (EPSRC-1788814), and the Cambridge European & Trinity Hall Scholarship in the case of Slawomir Tadeja. The second author, Pranay Seshadri, acknowledges the support of the United Kingdom Research and Innovation (UKRI) Strategic Priorities Fund, managed by the Engineering and Physical Sciences Research Council (EPSRC); grant number EP/T001569/1

Bare-handed 3D drawing in augmented reality

Head-mounted augmented reality (AR) enables embodied in situ drawing in three dimensions (3D).We explore 3D drawing interactions based on uninstrumented, unencumbered (bare) hands that preserve the user’s ability to freely navigate and interact with the physical environment. We derive three alternative interaction techniques supporting bare-handed drawing in AR from the literature and by analysing several envisaged use cases. The three interaction techniques are evaluated in a controlled user study examining three distinct drawing tasks: planar drawing, path description, and 3D object reconstruction. The results indicate that continuous freehand drawing supports faster line creation than the control point-based alternatives, although with reduced accuracy. User preferences for the different techniques are mixed and vary considerably between the different tasks, highlighting the value of diverse and flexible interactions. The combined effectiveness of these three drawing techniques is illustrated in an example application of 3D AR drawing