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Warehouse And Logistics: Smart Picking With Vuzix Smart Glasses, Elise Hemink 2022 Vuzix Corporation

Warehouse And Logistics: Smart Picking With Vuzix Smart Glasses, Elise Hemink

Frameless

Vuzix is an industry leader in augmented reality (AR) technology. We provide innovative products to an array of industries, a few being defense, security, enterprise, and consumers. Our AR technology provides a perfect balance of engagement in the digital and real worlds thanks to their innovative optics, AI apps and 5G capability.


Been Set Free: A Distributed Virtual Theatre Dance Performance, Joe Geigel 2022 Rochester Institute of Technology

Been Set Free: A Distributed Virtual Theatre Dance Performance, Joe Geigel

Frameless

For Frameless 2021, we present a fully realized example of virtual theatre. We define virtual theatre as a live theatrical performance, experienced on a stage in virtual reality, with participants in different physical locations (Geigel 2018).


Changeling Vr, Elouise Oyzon 2022 Rochester Institute of Technology

Changeling Vr, Elouise Oyzon

Frameless

Changeling VR is an interactive virtual reality narrative game. As we progress through the game, each level is seen through the Point of View of a different character whose emotional core is expressed through different aesthetics, mechanics and interactions.


Jet Of Blood Vr: First Playable Demo, Elizabeth Goins, Andy Head, Mason Hayes 2022 Rochester Institute of Technology

Jet Of Blood Vr: First Playable Demo, Elizabeth Goins, Andy Head, Mason Hayes

Frameless

A VR staging of Anonin Artaud’s 1925 surrealist play, Jet of Blood. The project experiments with virtual reality as a means to reimagine performance and frame the player, the audience, as actor. Ideas from Artaud’s philosophy such as the Theatre of Cruelty are incorporated along with spatial storytelling and game design. The project also seeks to expand accessibility to deaf and hard of hearing audiences through use of particle and text effects to visually express audio and sound.


The Studio X Karp Library Fellows: Peer-To-Peer Xr Learning & Engagement, Ayiana Crabtree, Muhammed El-Sayed, Nefle N. Oruç 2022 University of Rochester

The Studio X Karp Library Fellows: Peer-To-Peer Xr Learning & Engagement, Ayiana Crabtree, Muhammed El-Sayed, Nefle N. Oruç

Frameless

No abstract provided.


Creating A Virtual Reality Experience In Service To A Non-Profit Agency, Frank Deese, Susan Lakin, Isabelle Anderson 2022 Rochester Institute of Technology

Creating A Virtual Reality Experience In Service To A Non-Profit Agency, Frank Deese, Susan Lakin, Isabelle Anderson

Frameless

In the summer of 2018, RIT Professors Susan Lakin and Frank Deese discussed with the principal officers of the Society for the Protection and Care of Children (SPCC) in Rochester how the new technology of Virtual Reality might be used to not only impart information to viewers, but generate empathy for those receiving services from the organization as well as those performing those services. Their ultimate goal was to create an experience that could be viewed with VR headsets at fundraising events and on a website using low-cost Google Cardboard.


A Review Of Xr Classrooms In Institutions Of Higher Education, Brandon Patterson, Tallie Casucci 2022 University of Utah

A Review Of Xr Classrooms In Institutions Of Higher Education, Brandon Patterson, Tallie Casucci

Frameless

This talk will review the literature and examine existing physical spaces using virtual reality (VR) and augmented reality (AR), often referred together as extended reality (XR), to teach learners in an academic setting. Attendees will better understand best practices and ways of addressing potential challenges when designing a physical XR classroom space for higher education. A physical XR classroom provides institutions with a dedicated space for educational courses and workshops, which utilize XR for both one- off sessions and an entire semester (Pirker, Holly, and Gütl 2020). The talk will help answer the question, why a dedicated XR classroom?


A Web User Interface Image Processing Tool For Classifying The Extent Of Dementia Across Alzheimer’S, sathvik prasad palyam, Robin Ghosh 2022 Arkansas Tech University

A Web User Interface Image Processing Tool For Classifying The Extent Of Dementia Across Alzheimer’S, Sathvik Prasad Palyam, Robin Ghosh

ATU Research Symposium

Alzheimer's disease (AD) is the most common form of dementia. This project used four image specifications to classify the dementia stages in each patient applying the CNN algorithm. Employing the CNN-based in silico model, the authors successfully classified and predicted the different AD stages and got around 97.19% accuracy. Later, a web interface tool was developed to educate doctors or researchers to check the patients' dementia level based on the MRI brain images and suggest symptoms that strengthen the predicted level of AI. A user uploads the brain scan, which is sent to the backend server, where the image is …


The Illusion Of Agency In Human–Computer Interaction, Michael Madary 2022 University of the Pacific

The Illusion Of Agency In Human–Computer Interaction, Michael Madary

College of the Pacific Faculty Articles

This article makes the case that our digital devices create illusions of agency. There are times when users feel as if they are in control when in fact they are merely responding to stimuli on the screen in predictable ways. After the introduction, the second section of the article offers examples of illusions of agency that do not involve human–computer interaction in order to show that such illusions are possible and not terribly uncommon. The third and fourth sections of the article cover relevant work from empirical psychology, including the cues that are known to generate the sense of agency. …


Comai: Enabling Lightweight, Collaborative Intelligence By Retrofitting Vision Dnns, Kasthuri JAYARAJAH, Dhanuja WANNIARACHCHIGE, Tarek ABDELZAHER, Urbana CHAMPAIGN, Archan MISRA 2022 Singapore Management University

Comai: Enabling Lightweight, Collaborative Intelligence By Retrofitting Vision Dnns, Kasthuri Jayarajah, Dhanuja Wanniarachchige, Tarek Abdelzaher, Urbana Champaign, Archan Misra

Research Collection School Of Computing and Information Systems

While Deep Neural Network (DNN) models have transformed machine vision capabilities, their extremely high computational complexity and model sizes present a formidable deployment roadblock for AIoT applications. We show that the complexity-vs-accuracy-vs-communication tradeoffs for such DNN models can be significantly addressed via a novel, lightweight form of “collaborative machine intelligence” that requires only runtime changes to the inference process. In our proposed approach, called ComAI, the DNN pipelines of different vision sensors share intermediate processing state with one another, effectively providing hints about objects located within their mutually-overlapping Field-of-Views (FoVs). CoMAI uses two novel techniques: (a) a secondary shallow ML …


Trend: Temporal Event And Node Dynamics For Graph Representation Learning, Zhihao WEN, Yuan FANG 2022 Singapore Management University

Trend: Temporal Event And Node Dynamics For Graph Representation Learning, Zhihao Wen, Yuan Fang

Research Collection School Of Computing and Information Systems

Temporal graph representation learning has drawn significant attention for the prevalence of temporal graphs in the real world. However, most existing works resort to taking discrete snapshots of the temporal graph, or are not inductive to deal with new nodes, or do not model the exciting effects which is the ability of events to influence the occurrence of another event. In this work, We propose TREND, a novel framework for temporal graph representation learning, driven by TempoRal Event and Node Dynamics and built upon a Hawkes process-based graph neural network (GNN). TREND presents a few major advantages: (1) it is …


Gesturelens: Visual Analysis Of Gestures In Presentation Videos, Haipeng ZENG, Xingbo WANG, Yong WANG, Aoyu WU, Ting Chuen PONG, Huamin QU 2022 Singapore Management University

Gesturelens: Visual Analysis Of Gestures In Presentation Videos, Haipeng Zeng, Xingbo Wang, Yong Wang, Aoyu Wu, Ting Chuen Pong, Huamin Qu

Research Collection School Of Computing and Information Systems

Appropriate gestures can enhance message delivery and audience engagement in both daily communication and public presentations. In this paper, we contribute a visual analytic approach that assists professional public speaking coaches in improving their practice of gesture training through analyzing presentation videos. Manually checking and exploring gesture usage in the presentation videos is often tedious and time-consuming. There lacks an efficient method to help users conduct gesture exploration, which is challenging due to the intrinsically temporal evolution of gestures and their complex correlation to speech content. In this paper, we propose GestureLens, a visual analytics system to facilitate gesture-based and …


On Size-Oriented Long-Tailed Graph Classification Of Graph Neural Networks, Zemin LIU, Qiheng MAO, Chenghao LIU, Yuan FANG, Jianling SUN 2022 Singapore Management University

On Size-Oriented Long-Tailed Graph Classification Of Graph Neural Networks, Zemin Liu, Qiheng Mao, Chenghao Liu, Yuan Fang, Jianling Sun

Research Collection School Of Computing and Information Systems

The prevalence of graph structures attracts a surge of investigation on graph data, enabling several downstream tasks such as multigraph classification. However, in the multi-graph setting, graphs usually follow a long-tailed distribution in terms of their sizes, i.e., the number of nodes. In particular, a large fraction of tail graphs usually have small sizes. Though recent graph neural networks (GNNs) can learn powerful graph-level representations, they treat the graphs uniformly and marginalize the tail graphs which suffer from the lack of distinguishable structures, resulting in inferior performance on tail graphs. To alleviate this concern, in this paper we propose a …


Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price 2022 Air Force Institute of Technology

Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price

Theses and Dissertations

Increased levels of time are spent indoors, decreasing human interaction with nature and degrading photoentrainment, the synchronization of circadian rhythms with daylight variation. Military imagery analysts, among other professionals, are required to work in low light level environments to limit power consumption or increase contrast on display screens to improve detail detection. Insufficient exposure to light in these environments results in inadequate photoentrainment which is associated with degraded alertness and negative health effects. Recent research has shown that both the illuminance (i.e., perceived intensity) and wavelength of light affect photoentrainment. Simultaneously, modern lighting technologies have improved our ability to construct …


The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold 2022 Air Force Institute of Technology

The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold

Theses and Dissertations

Traditional control mechanisms restrict human input on the displays in 5th generation aircraft. This research explored methods for enhancing pilot interaction with large, information dense cockpit displays; specifically, the effects of visual feedback and control button configuration when augmenting cursor control with head tracking technology. Previous studies demonstrated that head tracking can be combined with traditional cursor control to decrease selection times but can increase pilot mental and physical workload. A human subject experiment was performed to evaluate two control button configurations and three visual feedback conditions. A Fitts Law analysis was performed to create predictive models of selection time …


A Thematic And Reference Analysis Of Touchless Technologies, Eric R. Curia 2022 Air Force Institute of Technology

A Thematic And Reference Analysis Of Touchless Technologies, Eric R. Curia

Theses and Dissertations

The purpose of this research is to explore the utility and current state of touchless technologies. Five categories of technologies are identified as a result of collecting and reviewing literature: facial/biometric recognition, gesture recognition, touchless sensing, personal devices, and voice recognition. A thematic analysis was conducted to evaluate the advantages and disadvantages of the five categories. A reference analysis was also conducted to determine the similarities between articles in each category. Touchless sensing showed to have the most advantages and least similar references. Gesture recognition was the opposite. Comparing analyses shows more reliable technology types are more beneficial and diverse.


The Application Of Virtual Reality In Firefighting Training, Dylan A. Gagnon 2022 Air Force Institute of Technology

The Application Of Virtual Reality In Firefighting Training, Dylan A. Gagnon

Theses and Dissertations

Immersive simulations such as virtual reality is becoming more prevalent for use in training environments for many professions. United States Air Force firefighters may benefit from incorporating VR technology into their training program to increase organizational commitment, job satisfaction, self-efficacy, and job performance. With implementing a new training platform, it is also important to understand the relationship between these variables and the perceived benefits and efficacy of the VR training, which has not yet been studied in previous research. This study addresses this issue by gathering data from fire departments currently fielding a VR fire training platform.


Mrim: Enabling Mixed-Resolution Imaging For Low-Power Pervasive Vision Tasks, Jiyan WU, Vithurson SUBASHARAN, Tuan TRAN, Archan MISRA 2022 Singapore Management University

Mrim: Enabling Mixed-Resolution Imaging For Low-Power Pervasive Vision Tasks, Jiyan Wu, Vithurson Subasharan, Tuan Tran, Archan Misra

Research Collection School Of Computing and Information Systems

While many pervasive computing applications increasingly utilize real-time context extracted from a vision sensing infrastructure, the high energy overhead of DNN-based vision sensing pipelines remains a challenge for sustainable in-the-wild deployment. One common approach to reducing such energy overheads is the capture and transmission of lower-resolution images to an edge node (where the DNN inferencing task is executed), but this results in an accuracy-vs-energy tradeoff, as the DNN inference accuracy typically degrades with a drop in resolution. In this work, we introduce MRIM, a simple but effective framework to tackle this tradeoff. Under MRIM, the vision sensor platform first executes …


Debiasing Nlu Models Via Causal Intervention And Counterfactual Reasoning, Bing TIAN, Yixin CAO, Yong ZHANG, Chunxiao XING 2022 Singapore Management University

Debiasing Nlu Models Via Causal Intervention And Counterfactual Reasoning, Bing Tian, Yixin Cao, Yong Zhang, Chunxiao Xing

Research Collection School Of Computing and Information Systems

Recent studies have shown that strong Natural Language Understanding (NLU) models are prone to relying on annotation biases of the datasets as a shortcut, which goes against the underlying mechanisms of the task of interest. To reduce such biases, several recent works introduce debiasing methods to regularize the training process of targeted NLU models. In this paper, we provide a new perspective with causal inference to fnd out the bias. On the one hand, we show that there is an unobserved confounder for the natural language utterances and their respective classes, leading to spurious correlations from training data. To remove …


Deconfounded Visual Grounding, Jianqiang HUANG, Yu QIN, Jiaxin QI, Qianru SUN, Hanwang ZHANG 2022 Singapore Management University

Deconfounded Visual Grounding, Jianqiang Huang, Yu Qin, Jiaxin Qi, Qianru Sun, Hanwang Zhang

Research Collection School Of Computing and Information Systems

We focus on the confounding bias between language and location in the visual grounding pipeline, where we find that the bias is the major visual reasoning bottleneck. For example, the grounding process is usually a trivial languagelocation association without visual reasoning, e.g., grounding any language query containing sheep to the nearly central regions, due to that most queries about sheep have groundtruth locations at the image center. First, we frame the visual grounding pipeline into a causal graph, which shows the causalities among image, query, target location and underlying confounder. Through the causal graph, we know how to break the …


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