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Probabilistic Roadmaps For Virtual Camera Pathing With Cinematographic Principles, Katherine Davis 2017 California Polytechnic State University, San Luis Obispo

Probabilistic Roadmaps For Virtual Camera Pathing With Cinematographic Principles, Katherine Davis

Master's Theses

As technology use increases in the world and inundates everyday life, the visual aspect of technology or computer graphics becomes increasingly important. This thesis presents a system for the automatic generation of virtual camera paths for fly-throughs of a digital scene. The sample scene used in this work is an underwater setting featuring a shipwreck model with other virtual underwater elements such as rocks, bubbles and caustics. The digital shipwreck model was reconstructed from an actual World War II shipwreck, resting off the coast of Malta. Video and sonar scans from an autonomous underwater vehicle were used in a photogrammetry …


Music Times: A Music Learning Game, Emily Woo 2017 California Polytechnic State University, San Luis Obispo

Music Times: A Music Learning Game, Emily Woo

Computer Science and Software Engineering

Music Times is a two dimensional educational video game with the purpose of gamifying learning of musical concepts. It has elements of adventure and visual novel games, and incentivizes the player to learn music to explore new levels. It is developed in the Unity game engine, scripted in C#, and targeted for mobile devices. It has six working levels: three lesson levels and three corresponding challenge levels. Each level contains slight differences in visual and aural feel.


Feature Learning Via Partial Differential Equation With Applications To Face Recognition, Cong FANG, Zhenyu ZHAO, Pan ZHOU, Zhouchen LIN 2017 Singapore Management University

Feature Learning Via Partial Differential Equation With Applications To Face Recognition, Cong Fang, Zhenyu Zhao, Pan Zhou, Zhouchen Lin

Research Collection School Of Computing and Information Systems

Feature learning is a critical step in pattern recognition, such as image classification. However, most of the existing methods cannot extract features that are discriminative and at the same time invariant under some transforms. This limits the classification performance, especially in the case of small training sets. To address this issue, in this paper we propose a novel Partial Differential Equation (PDE) based method for feature learning. The feature learned by our PDE is discriminative, also translationally and rotationally invariant, and robust to illumination variation. To our best knowledge, this is the first work that applies PDE to feature learning …


Using Intel Realsense Depth Data For Hand Tracking In Unreal Engine 4, Granger Lang 2017 California Polytechnic State University, San Luis Obispo

Using Intel Realsense Depth Data For Hand Tracking In Unreal Engine 4, Granger Lang

Liberal Arts and Engineering Studies

This project describes how to build a hand tracking method for VR/AR using the raw data from a depth sensing camera.


Active Video Summarization: Customized Summaries Via On-Line Interaction With The User, Ana Garcia DEL MOLINO, Xavier BOIX, Joo-Hwee LIM, Ah-hwee TAN 2017 Singapore Management University

Active Video Summarization: Customized Summaries Via On-Line Interaction With The User, Ana Garcia Del Molino, Xavier Boix, Joo-Hwee Lim, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

To facilitate the browsing of long videos, automatic video summarization provides an excerpt that represents its content. In the case of egocentric and consumer videos, due to their personal nature, adapting the summary to specific user’s preferences is desirable. Current approaches to customizable video summarization obtain the user’s preferences prior to the summarization process. As a result, the user needs to manually modify the summary to further meet the preferences. In this paper, we introduce Active Video Summarization (AVS), an interactive approach to gather the user’s preferences while creating the summary. AVS asks questions about the summary to update it …


Empath-D: Empathetic Design For Accessibility, Kenny Tsu Wei CHOO, Rajesh Krishna BALAN, Kiat Wee TAN, Archan MISRA, Youngki LEE 2017 Singapore Management University

Empath-D: Empathetic Design For Accessibility, Kenny Tsu Wei Choo, Rajesh Krishna Balan, Kiat Wee Tan, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

We describe our vision for Empath-D, our system to enable Empathetic User Interface Design. Our key idea is to leverage Virtual and Augmented Reality (VR / AR) displays to provide an Immersive Reality environment, where developers/designers can emulate impaired interactions by elderly or disabled users while testing the usability of their applications. Our early experiences with the Empath-D prototype show that Empath-D can emulate a cataract vision impairment of the elderly and guide designers to create accessible web pages with less mental workload.


Unsupervised Visual Hashing With Semantic Assistant For Content-Based Image Retrieval, Lei ZHU, Jialie SHEN, Liang XIE, Zhiyong CHENG 2017 Singapore Management University

Unsupervised Visual Hashing With Semantic Assistant For Content-Based Image Retrieval, Lei Zhu, Jialie Shen, Liang Xie, Zhiyong Cheng

Research Collection School Of Computing and Information Systems

As an emerging technology to support scalable content-based image retrieval (CBIR), hashing has recently received great attention and became a very active research domain. In this study, we propose a novel unsupervised visual hashing approach called semantic-assisted visual hashing (SAVH). Distinguished from semi-supervised and supervised visual hashing, its core idea is to effectively extract the rich semantics latently embedded in auxiliary texts of images to boost the effectiveness of visual hashing without any explicit semantic labels. To achieve the target, a unified unsupervised framework is developed to learn hash codes by simultaneously preserving visual similarities of images, integrating the semantic …


Static Human Detection And Scenario Recognition Via Wearable Thermal Sensing System, Qingquan Sun, Ju Shen, Haiyan Qiao, Xinlin Huang, Chen Chen, Fei Hu 2017 California State University - San Bernardino

Static Human Detection And Scenario Recognition Via Wearable Thermal Sensing System, Qingquan Sun, Ju Shen, Haiyan Qiao, Xinlin Huang, Chen Chen, Fei Hu

Computer Science Faculty Publications

Conventional wearable sensors are mainly used to detect the physiological and activity information of individuals who wear them, but fail to perceive the information of the surrounding environment. This paper presents a wearable thermal sensing system to detect and perceive the information of surrounding human subjects. The proposed system is developed based on a pyroelectric infrared sensor. Such a sensor system aims to provide surrounding information to blind people and people with weak visual capability to help them adapt to the environment and avoid collision. In order to achieve this goal, a low-cost, low-data-throughput binary sampling and analyzing scheme is …


Older Adult Health: National Library Of Medicine Resources For Health Care Providers And For Patients And Families, Elizabeth Dyer, Barbara Swartzlander, Marilyn R. Gugliucci, Laura Taylor 2017 University of New England

Older Adult Health: National Library Of Medicine Resources For Health Care Providers And For Patients And Families, Elizabeth Dyer, Barbara Swartzlander, Marilyn R. Gugliucci, Laura Taylor

Library Services Faculty Publications

This list of resources was designed to complement a project funded by the National Network of Libraries of Medicine (NN/LM) New England Region (NER) entitled “Empathy Learned Through an Extended Medical Education Virtual Reality Project." The project used a virtual reality (VR) experience for 1st year medical students developed by Embodied Labs. The interactive “Alfred Lab” immerses users in the story of a 74-year-old patient who has macular degeneration and hearing loss, allowing users to experience these conditions from the patient’s perspective as he interacts with his family and doctor.


Unboxing Cluster Heatmaps, Sophie J. Engle, S. Whalen, Alark Joshi, K. Pollard 2017 University of San Francisco

Unboxing Cluster Heatmaps, Sophie J. Engle, S. Whalen, Alark Joshi, K. Pollard

Computer Science

Background: Cluster heatmaps are commonly used in biology and related fields to reveal hierarchical clusters in data matrices. This visualization technique has high data density and reveal clusters better than unordered heatmaps alone. However, cluster heatmaps have known issues making them both time consuming to use and prone to error. We hypothesize that visualization techniques without the rigid grid constraint of cluster heatmaps will perform better at clustering-related tasks.

Results: We developed an approach to “unbox” the heatmap values and embed them directly in the hierarchical clustering results, allowing us to use standard hierarchical visualization techniques as alternatives …


A System To Monitor Cognitive Workload In Naturalistic High-Motion Environments, Bethany K. Bracken, Seth Elkin-Frankston, Noa Palmon, Michael Farry, Blaise de B Frederick 2017 Charles River Analytics

A System To Monitor Cognitive Workload In Naturalistic High-Motion Environments, Bethany K. Bracken, Seth Elkin-Frankston, Noa Palmon, Michael Farry, Blaise De B Frederick

H-Workload 2017: Models and Applications (Works in Progress)

Across many careers, individuals face alternating periods of high and low attention and cognitive workload can impair cognitive function and undermine job performance. We have designed and are developing an unobtrusive system to Monitor, Extract, and Decode Indicators of Cognitive Workload (MEDIC) in naturalistic, high-motion environments. MEDIC is designed to warn individuals, teammates, or supervisors when steps should be taken to augment cognitive readiness. We first designed and manufactured a forehead sensor device that includes a custom fNIRS sensor and a three-axis accelerometer designed to be mounted on the inside of a baseball cap or headband, or standard issue gear …


Towards A Not Obtrusive Low Cost Biosystem To Assess Risk Perception In Workplace Through Stress Detection, Emanuele Bellini, Serena Benevenuti, Chiara Batistini 2017 LOGOS Ricerca & Innovazione, Florence

Towards A Not Obtrusive Low Cost Biosystem To Assess Risk Perception In Workplace Through Stress Detection, Emanuele Bellini, Serena Benevenuti, Chiara Batistini

H-Workload 2017: Models and Applications (Works in Progress)

The main aim of the article is to build a method to assess risk perception in real time in order to early detect and prevent risk behaviors and possible human errors. To this end, the relation between mental workload and stress as critical factors affecting risk perception has been investigated. In particular the mental-physical activation generated by an increment of the workload has the effect of reducing the resources needed to perceive risk increasing the worker vulnerability. The complexity of the stress phenomenon suggested the adoption of an integrated view. The Functional Model has been adopted to for its holistic …


Reducing Peak Workload In The Cockpit: A Human In The Loop Simulation Evaluating New Runway Selection Tool, Tanja Bos, Rolf Zon, Wilfred Rouwhorst 2017 NLR-Netherlands Aerospace Centre

Reducing Peak Workload In The Cockpit: A Human In The Loop Simulation Evaluating New Runway Selection Tool, Tanja Bos, Rolf Zon, Wilfred Rouwhorst

H-Workload 2017: Models and Applications (Works in Progress)

In efforts to increase safety and reduce peak workload situations in the cockpit, a tool with a different interaction style was developed for use in case of a runway change instructed by Air Traffic Control during approach. In an experiment a workload comparison was made between the new tool and the conventional cockpit. Workload was measured by means of a self-rating after each experiment run, as well as eye blink frequency during each run. Results show that the self-rated workload decreases with the new tool for one of the two crew members and the blink frequency suggests a workload decrease …


System Identification Of Motion Artifact: Noise In Eeg Headsets From Locomotion, Kaela Shea, James Tung 2017 University of Waterloo, Canada

System Identification Of Motion Artifact: Noise In Eeg Headsets From Locomotion, Kaela Shea, James Tung

H-Workload 2017: Models and Applications (Works in Progress)

Fall prevention for geriatric populations is a growing concern among clinicians and researchers due to severe risk of morbidity and loss of independence. Emerging evidence has demonstrated that mental workload while walking influences gait stability and the risk for falling. Electroencephalography (EEG) presents a potential method to provide objective measures of mental workload, particularly during daily activities. Noise introduced to the EEG signal during motion, however, is restrictive. The study presented in the following paper isolates EEG signal noise attained from gait for a commercially accessible EEG system, the "Emotiv" Time and spectral system identification techniques were applied to model …


Online Measuring Of Available Resources, Enrique Munoz-de-Escalona, José Juan Canas 2017 University of Granada

Online Measuring Of Available Resources, Enrique Munoz-De-Escalona, José Juan Canas

H-Workload 2017: Models and Applications (Works in Progress)

This paper present a proposal for measuring available mental resources during the accomplishment of a task. Our proposal consists in measuring emotions provoked by perceived self-efficacy in the execution of the task. Self-efficacy is one of the most important factors that affect the resources that a person puts at the disposal of the execution of the task. When a person perceives that he/she is not being effective he/she will activate more resources to improve his performance. This self-efficacy will be reflected in the emotions that the person experiences. A good efficacy will provoke positive emotions and a bad efficacy negative …


Hindsight: Encouraging Exploration Through Direct Encoding Of Personal Interaction History, MI Feng, Cheng Deng, Evan M. Peck, Lane Harrison 2017 Worcester Polytechnic Institute

Hindsight: Encouraging Exploration Through Direct Encoding Of Personal Interaction History, Mi Feng, Cheng Deng, Evan M. Peck, Lane Harrison

Faculty Journal Articles

Physical and digital objects often leave markers of our use. Website links turn purple after we visit them, for example, showing us information we have yet to explore. These “footprints” of interaction offer substantial benefits in information saturated environments - they enable us to easily revisit old information, systematically explore new information, and quickly resume tasks after interruption. While applying these design principles have been successful in HCI contexts, direct encodings of personal interaction history have received scarce attention in data visualization. One reason is that there is little guidance for integrating history into visualizations where many visual channels are …


A Workload-Centered Perspective On Reduced Crew Operations In Commercial Aviation, Daniela Schmid 2017 DLR-German Aerospace Centre

A Workload-Centered Perspective On Reduced Crew Operations In Commercial Aviation, Daniela Schmid

H-Workload 2017: Models and Applications (Works in Progress)

Mental workload of a pilot, in short workload, depends on various characteristics of different accumulated tasks on the flight deck. Exogenous task demands and endogenous supply of attentional or information processing resources determine workload [1]. Performance is expect to drop if the demand exceeds the available resources of the pilot. Expertise and experience modulate the endogenous sup- ply of resources like perceiving, updating memory, planing, making a decision, and executing and processing a response. Subsequently, workload manifests in performance variables, subjective experience, and physiological parameters [2]. This is how we can summarize workload very brie y to introduce a model …


A Pilot Study Into Bio-Behavioural Measurements On Air Traffic Controllers In Remote Tower Operations, Tanja Bos, Rolf Zon, Eszter Furedi, Dezso Dudas, Daniel Rohacs 2017 NLR-Netherlands Aerospace Centre

A Pilot Study Into Bio-Behavioural Measurements On Air Traffic Controllers In Remote Tower Operations, Tanja Bos, Rolf Zon, Eszter Furedi, Dezso Dudas, Daniel Rohacs

H-Workload 2017: Models and Applications (Works in Progress)

What is the impact of shifting to remote tower operations on the Air Traffic Controller? In the joint HungaroControl-Netherlands Aerospace Centre NLR pilot project an assessment of bio-behaviour on three air traffic controllers was made in a remote tower and conventional tower. The research is motivated by HungaroControl’s plans in shifting to remote tower operations at Budapest airport in the upcoming years. This pilot project is considered a feasibility study to investigate if an eye tracker and a heart rate sensor can be used to derive workload, the controllers’ division of attention over information elements, and scanning strategies in two …


A Systems Approach To Predicting And Measuring Workload In Rail Traffic Management Systems, Joanna Evans 2017 Thales GTS, Human Factor Engineer

A Systems Approach To Predicting And Measuring Workload In Rail Traffic Management Systems, Joanna Evans

H-Workload 2017: Models and Applications (Works in Progress)

The introduction of systems such as Traffic Management (TM) will result in a number of changes in how the railway is managed for operations and maintenance staff such as, an increase in collaborative working styles and shared responsibilities. In order to react to these changing operational demands and user needs, TM workstation designs need to have greater flexibility and be configurable to support the information requirements for each specific role as well as support each role during different scenarios. Although this flexibility in system design has the potential to enhance performance, it increases the complexity of measuring operator workload. The …


Correcting Pedestrian Dead Reckoning With Monte Carlo Localization Boxed For Indoor Navigation, Akira T. Murphy 2017 Colby College

Correcting Pedestrian Dead Reckoning With Monte Carlo Localization Boxed For Indoor Navigation, Akira T. Murphy

Honors Theses

Localization of phones is a ubiquitous part of the modern mobile electronics landscape. However, there are many situations where the current method of networked localization fails. A Pedestrian Dead Reckoning System where the location of the user is calculated by counting the steps and direction of the user was implemented as an iOS app with python for data analysis. A novel algorithm for wireless sensor localization using Ad-Hoc Bluetooth networks was proposed. A small experiment was performed proving that the system is nearly equal to state of the art algorithms.


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