Graphics and Human Computer Interfaces Commons^™

Co-Design Of An Interactive Wellness Park: Exploring Design Requirements For A Multimodal Outdoor Physical Web Installation With Older Adults, Fatima Badmos

Academic Posters Collection

The global demographic landscape is experiencing a notable shift, characterised by a growing proportion of adults over 60. According to projections, the proportion of individuals aged 60 and above is expected to reach one-sixth of the global population by 2030. Furthermore, by 2050, this demographic is projected to exceed a staggering two billion people. Amidst this shift, there is an urgent need to develop interactive and innovative solutions to address older adults' unique challenges, particularly in outdoor physical activity.

A co-design methodology involving older adults’ participation from the idea generation to the application development process will be adopted to address …

Evaluating Human Eye Features For Objective Measure Of Working Memory Capacity, Yasasi Abeysinghe, Enkelejda Kasneci (Ed.), Frederick Shic (Ed.), Mohamed Khamis (Ed.)

Computer Science Faculty Publications

Eye tracking measures can provide means to understand the underlying development of human working memory. In this study, we propose to develop machine learning algorithms to find an objective relationship between human eye movements via oculomotor plant and their working memory capacity, which determines subjective cognitive load. Here we evaluate oculomotor plant features extracted from saccadic eye movements, traditional positional gaze metrics, and advanced eye metrics such as ambient/focal coefficient , gaze transition entropy, low/high index of pupillary activity (LHIPA), and real-time index of pupillary activity (RIPA). This paper outlines the proposed approach of evaluating eye movements for obtaining an …

Distance Based Image Classification: A Solution To Generative Classification’S Conundrum?, Wen-Yan Lin, Siying Liu, Bing Tian Dai, Hongdong Li

Research Collection School Of Computing and Information Systems

Most classifiers rely on discriminative boundaries that separate instances of each class from everything else. We argue that discriminative boundaries are counter-intuitive as they define semantics by what-they-are-not; and should be replaced by generative classifiers which define semantics by what-they-are. Unfortunately, generative classifiers are significantly less accurate. This may be caused by the tendency of generative models to focus on easy to model semantic generative factors and ignore non-semantic factors that are important but difficult to model. We propose a new generative model in which semantic factors are accommodated by shell theory’s [25] hierarchical generative process and non-semantic factors by …

Taurus: Towards A Unified Force Representation And Universal Solver For Graph Layout, Mingliang Xue, Zhi Wang, Fahai Zhong, Yong Wang, Mingliang Xu, Oliver Deussen, Yunhai Wang

Research Collection School Of Computing and Information Systems

Over the past few decades, a large number of graph layout techniques have been proposed for visualizing graphs from various domains. In this paper, we present a general framework, Taurus, for unifying popular techniques such as the spring-electrical model, stress model, and maxent-stress model. It is based on a unified force representation, which formulates most existing techniques as a combination of quotient-based forces that combine power functions of graph-theoretical and Euclidean distances. This representation enables us to compare the strengths and weaknesses of existing techniques, while facilitating the development of new methods. Based on this, we propose a new balanced …

Enabling Customization Of Discussion Forums For Blind Users, Mohan Sunkara, Yash Prakash, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions …

Autodesc: Facilitating Convenient Perusal Of Web Data Items For Blind Users, Yash Prakash, Mohan Sunkara, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Web data items such as shopping products, classifieds, and job listings are indispensable components of most e-commerce websites. The information on the data items are typically distributed over two or more webpages, e.g., a ‘Query-Results’ page showing the summaries of the items, and ‘Details’ pages containing full information about the items. While this organization of data mitigates information overload and visual cluttering for sighted users, it however increases the interaction overhead and effort for blind users, as back-and-forth navigation between webpages using screen reader assistive technology is tedious and cumbersome. Existing usability-enhancing solutions are unable to provide adequate support in …

Mwirgan: Unsupervised Visible-To Mwir Image Translation With Generative Adversarial Network, Mohammad Shahab Uddin, Chiman Kwan, Jiang Li

Electrical & Computer Engineering Faculty Publications

Unsupervised image-to-image translation techniques have been used in many applications, including visible-to-Long-Wave Infrared (visible-to-LWIR) image translation, but very few papers have explored visible-to-Mid-Wave Infrared (visible-to-MWIR) image translation. In this paper, we investigated unsupervised visible-to-MWIR image translation using generative adversarial networks (GANs). We proposed a new model named MWIRGAN for visible-to-MWIR image translation in a fully unsupervised manner. We utilized a perceptual loss to leverage shape identification and location changes of the objects in the translation. The experimental results showed that MWIRGAN was capable of visible-to-MWIR image translation while preserving the object’s shape with proper enhancement in the translated images and …

The Impact Of Pre-Experiment Walking On Distance Perception In Vr, Soheil Sepahyar

Dissertations, Master's Theses and Master's Reports

While individuals can accurately estimate distances in the real world, this ability is often diminished in virtual reality (VR) simulations, hampering performance across training, entertainment, prototyping, and education domains. To assess distance judgments, the direct blind walking method—having participants walk blindfolded to targets—is frequently used. Typically, direct blind walking measurements are performed after an initial practice phase, where people become comfortable with walking while blindfolded. Surprisingly, little research has explored how such pre-experiment walking impacts subsequent VR distance judgments. Our initial investigation revealed increased pre-experiment blind walking reduced distance underestimations, underscoring the importance of detailing these preparatory procedures in research—details …

An Ambiguous Technique For Nonvisual Text Entry, Dylan C. Gaines

Dissertations, Master's Theses and Master's Reports

Text entry is a common daily task for many people, but it can be a challenge for people with visual impairments when using virtual touchscreen keyboards that lack physical key boundaries. In this thesis, we investigate using a small number of gestures to select from groups of characters to remove most or all dependence on touch locations. We leverage a predictive language model to select the most likely characters from the selected groups once a user completes each word.

Using a preliminary interface with six groups of characters based on a Qwerty keyboard, we find that users are able to …

Sensor Relationship Inference In Single Resident Smart Homes Using Time Series, Samuel Nack

Graduate Theses/Dissertations

Determining sensor relationships in smart environments is complex due to the variety and volume of time series information they provide. Moreover, identifying sensor relationships to connect them with actuators is difficult for smart home users who may not have technical experience. Yet, gathering information on sensor relationships is a crucial intermediate step towards more advanced smart home applications such as advanced policy generation or automatic sensor configuration. Therefore, in this thesis, I propose a novel unsupervised learning approach, named SeReIn, to automatically group sensors by their inherent relationships solely using time series data for single resident smart homes. SeReIn extracts …

Simulating Incompressible Thin-Film Fluid With A Moving Eulerian-Lagrangian Particle Method, Yitong Deng

Dartmouth College Master’s Theses

In this thesis, we introduce a Moving Eulerian-Lagrangian Particle (MELP) method, a mesh-free method to simulate incompressible thin-film fluid systems: soap bubbles, bubble clusters, and foams. The realistic simulation of such systems depends upon the successful treatment of three aspects: (1) the soap film's deformation due to the tendency to minimize the surface energy, giving rise to the bouncy characteristics of soap bubbles, (2) the tangential fluid flow on the thin film, causing the thickness to vary spatially, which in conjunction with thin-film interference creates evolving and highly sophisticated iridescent color patterns, (3) the topological changes due to collision, separation, …

An Interactive System For Generating Music From Moving Images, Hanlin Wang

Dartmouth College Master’s Theses

Moving images contain a wealth of information pertaining to motion. Motivated by the interconnectedness of music and movement, we present a framework for transforming the kinetic qualities of moving images into music. We developed an interactive software system that takes video as input and maps its motion attributes into the musical dimension based on perceptually grounded principles. The system combines existing sonification frameworks with theories and techniques of generative music. To evaluate the system, we conducted a two-part experiment. First, we asked participants to make judgements on video-audio correspondence from clips generated by the system. Second, we asked participants to …