Graphics and Human Computer Interfaces Commons^™

Using Virtual Reality To Improve Sitting Balance, Alice Kay Barnes

Graduate Theses/Dissertations

This thesis focuses on using virtual reality (VR) to enhance sitting balance and core strength. It is a study in how to create a VR exercise program which is interesting enough to keep players/patients motivated, but comfortable to play and not overwhelming to the senses. The software used for this study was written with the hope that a later version of it might be used with occupational/physical therapy patients one day. For this master’s thesis, the initial testing has been done with healthy volunteers. The software incorporates what developers know thus far about designing for VR, and it is hoped …

A Spatial Collaboration: Building A Multi-Institution Geospatial Data Discovery Portal, Mara Blake, Karen Majewicz, Ryan Mattke, Kathleen W. Weessies

Collaborative Librarianship

As academic education and research increasingly take advantage of geospatial data and methodologies, we see a corresponding exponential growth in the number of available geospatial resources in the form of GIS datasets and scanned historical maps. However, users can experience difficulty finding these resources due to the unconnected multitude of platforms and clearinghouses that host them. Additionally, the resources are not always well described with web semantic metadata that facilitates discovery. In response to this challenge, The Big Ten Academic Alliance Geospatial Data Project began in 2015 to provide discoverability, facilitate access, and connect scholars to geospatial resources. Our project …

Color-Sketch Simulator: A Guide For Color-Based Visual Known-Item Search, Jakub Lokoč, Anh Nguyen Phuong, Marta Vomlelová, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

In order to evaluate the effectiveness of a color-sketch retrieval system for a given multimedia database, tedious evaluations involving real users are required as users are in the center of query sketch formulation. However, without any prior knowledge about the bottlenecks of the underlying sketch-based retrieval model, the evaluations may focus on wrong settings and thus miss the desired effect. Furthermore, users have usually no clues or recommendations to draw color-sketches effectively. In this paper, we aim at a preliminary analysis to identify potential bottlenecks of a flexible color-sketch retrieval model. We present a formal framework based on position-color feature …

Vireo @ Trecvid 2017: Video-To-Text, Ad-Hoc Video Search And Video Hyperlinking, Phuong Anh Nguyen, Qing Li, Zhi-Qi Cheng, Yi-Jie Lu, Hao Zhang, Xiao Wu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

In this paper, we describe the systems developed for Video-to-Text (VTT), Ad-hoc Video Search (AVS) and Video Hyper-linking (LNK) tasks at TRECVID 2017 [1] and the achieved results.

Streaming Vr For Immersion: Quality Aspects Of Compressed Spatial Audio, Miroslaw Narbutt, Sean O’Leary, Andrew Allen, Jan Skoglund, Andrew Hines

Conference papers

Delivering a 360-degree soundscape that matches full sphere visuals is an essential aspect of immersive VR. Ambisonics is a full sphere surround sound technique that takes into account the azimuth and elevation of sound sources, portraying source location above and below as well as around the horizontal plane of the listener. In contrast to channel-based methods, ambisonics representation offers the advantage of being independent of a specific loudspeaker set-up. Streaming ambisonics over networks requires efficient encoding techniques that compress the raw audio content without compromising quality of experience (QoE). This work investigates the effect of audio channel compression via the …

Semantic Reasoning In Zero Example Video Event Retrieval, M. H. T. De Boer, Yi-Jie Lu, Hao Zhang, Klamer Schutte, Chong-Wah Ngo, Wessel Kraaij

Research Collection School Of Computing and Information Systems

Searching in digital video data for high-level events, such as a parade or a car accident, is challenging when the query is textual and lacks visual example images or videos. Current research in deep neural networks is highly beneficial for the retrieval of high-level events using visual examples, but without examples it is still hard to (1) determine which concepts are useful to pre-train (Vocabulary challenge) and (2) which pre-trained concept detectors are relevant for a certain unseen high-level event (Concept Selection challenge). In our article, we present our Semantic Event Retrieval Systemwhich (1) shows the importance of high-level concepts …

Pic2dish: A Customized Cooking Assistant System, Yongsheng An, Yu Cao, Jingjing Chen, Chong-Wah Ngo, Jia Jia, Huanbo Luan, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The art of cooking is always fascinating. Nevertheless, reproducing a delicious dish that one has never encountered before is not easy. Even if the name of dish is known and the corresponding recipe could be retrieved, the right ingredients for cooking the dish may not be available due to factors such as geography region or season. Furthermore, knowing how to cut, cook and control timing may be challenging for one whose has no cooking experience. In this paper, an all-around cooking assistant mobile app, named Pic2Dish, is developed to help users who would like to cook a dish but neither …

Cross-Modal Recipe Retrieval With Rich Food Attributes, Jingjing Chen, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Food is rich of visible (e.g., colour, shape) and procedural (e.g., cutting, cooking) attributes. Proper leveraging of these attributes, particularly the interplay among ingredients, cutting and cooking methods, for health-related applications has not been previously explored. This paper investigates cross-modal retrieval of recipes, specifically to retrieve a text-based recipe given a food picture as query. As similar ingredient composition can end up with wildly different dishes depending on the cooking and cutting procedures, the difficulty of retrieval originates from fine-grained recognition of rich attributes from pictures. With a multi-task deep learning model, this paper provides insights on the feasibility of …

Accessibility And Usability Of Government Websites In Tanzania, Joel S. Mtebe, Aron W. Kondoro

The African Journal of Information Systems

The government of Tanzania has been embracing information systems specifically websites in order to widen access to government services, lower administrative costs, and to increase public participation in decision making. As a result, almost every ministry, department, and agency (MDA) has developed a website of different kind. However, the majority of existing websites were developed without sufficiently considering user needs which indicates that they do have some usability and accessibility problems. This study used SortSite tool to evaluate accessibility and usability of government websites taking a sample of 22 websites. The report from the SortSite tool was then checked against …

An Efficient Image Segmentation Algorithm Using Neutrosophic Graph Cut, Florentin Smarandache, Yanhui Guo, Yaman Akbulut, Abdulkadir Sengur, Rong Xia

Branch Mathematics and Statistics Faculty and Staff Publications

Segmentation is considered as an important step in image processing and computer vision applications, which divides an input image into various non-overlapping homogenous regions and helps to interpret the image more conveniently. This paper presents an efficient image segmentation algorithm using neutrosophic graph cut (NGC). An image is presented in neutrosophic set, and an indeterminacy filter is constructed using the indeterminacy value of the input image, which is defined by combining the spatial information and intensity information. The indeterminacy filter reduces the indeterminacy of the spatial and intensity information. A graph is defined on the image and the weight for …

What Does Playing Games Teach Us About A Student's Ethical Life?, Robert Mccloud, Tamara Luarasi

WCBT Faculty Publications

Most of our students play video games. A substantial percentage of our students is required to take a computer ethics course before graduation. Both ACM and ABET require some form of computer ethics. This paper addresses gaming ethics as a subset of the computer ethics course. Specifically it considers the case of Grand Theft Auto (GTA), one of the most successful and most criticized game franchises. Through interviews with computer science students the study looks at mainstream reaction to GTA and finds that computer science students, probably one of the more sophisticated groups of gamers, have sometimes surprising ethical views …

Parallel Personalized Pagerank On Dynamic Graphs, Wentian Guo, Yuchen Li, Yuchen Li, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

Personalized PageRank (PPR) is a well-known proximitymeasure in graphs. To meet the need for dynamic PPRmaintenance, recent works have proposed a local updatescheme to support incremental computation. Nevertheless,sequential execution of the scheme is still too slow for highspeedstream processing. Therefore, we are motivated todesign a parallel approach for dynamic PPR computation.First, as updates always come in batches, we devise a batchprocessing method to reduce synchronization cost among everysingle update and enable more parallelism for iterativeparallel execution. Our theoretical analysis shows that theparallel approach has the same asymptotic complexity asthe sequential approach. Second, we devise novel optimizationtechniques to e↵ectively reduce runtime …

Card Tricks: A Workflow For Scalability And Dynamic Content Creation Using Paper2d And Unreal Engine 4, Owen Gottlieb, Dakota Herold, Edward Amidon

Presentations and other scholarship

In this paper, we describe the design and technological methods of

our dynamic sprite system in Lost & Found, a table-top-to-mobile

card game designed to improve literacy regarding prosocial

aspects of religious legal systems, specifically, collaboration and

cooperation. Harnessing the capabilities of Unreal Engine’s

Paper2D system, we created a dynamic content creation pipeline

that empowered our game designers so that they could rapidly

iterate on the game’s systems and balance externally from the

engine. Utilizing the Unreal Blueprint component system we were

also able to modularize each actor during runtime as data may be

changed. The technological approach behind Lost …

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

A Case Study For Ecampus Spatial: Business Data Exploration, James Carswell, Thanh Thao Pham Ti, Andrea Ballatore, Junjun Yin, Linh Truong-Hong

Books/Book chapters

Location based querying is the core interaction paradigm between mobile citizens and the Internet of Things, so providing users with intelligent web-services that interact efficiently with web and wireless devices to recommend personalised services is a key goal. With today's popular Web Map Services, users can ask for general information at a specific location, but not detailed information such as related functionality or environments. This shortcoming comes from a lack of connection between non-spatial “business” data and spatial “map” data. This chapter presents a novel approach for location-based querying in web and wireless environments, in which non-spatial business data is …

A Reliable And Efficient Wireless Sensor Network System For Water Quality Monitoring, Dung Nguyen, Phu Huu Phung

Computer Science Faculty Publications

Wireless sensor networks (WSNs) are strongly useful to monitor physical and environmental conditions to provide realtime information for improving environment quality. However, deploying a WSN in a physical environment faces several critical challenges such as high energy consumption, and data loss.In this work, we have proposed a reliable and efficient environmental monitoring system in ponds using wireless sensor network and cellular communication technologies. We have designed a hardware and software ecosystem that can limit the data loss yet save the energy consumption of nodes. A lightweight protocol acknowledges data transmission among the nodes. Data are transmitted to the cloud using …

Bridge Text And Knowledge By Learning Multi-Prototype Entity Mention Embedding, Yixin Cao, Lifu Huang, Heng Ji, Xu Chen, Juanzi Li

Research Collection School Of Computing and Information Systems

Integrating text and knowledge into a unified semantic space has attracted significant research interests recently. However, the ambiguity in the common space remains a challenge, namely that the same mention phrase usually refers to various entities. In this paper, to deal with the ambiguity of entity mentions, we propose a novel Multi-Prototype Mention Embedding model, which learns multiple sense embeddings for each mention by jointly modeling words from textual contexts and entities derived from a knowledge base. In addition, we further design an efficient language model based approach to disambiguate each mention to a specific sense. In experiments, both qualitative …

Formresnet: Formatted Residual Learning For Image Restoration, Jianbo Jiao, Wei-Chih Tu, Shengfeng He

Research Collection School Of Computing and Information Systems

In this paper, we propose a deep CNN to tackle the image restoration problem by learning the structured residual. Previous deep learning based methods directly learn the mapping from corrupted images to clean images, and may suffer from the gradient exploding/vanishing problems of deep neural networks. We propose to address the image restoration problem by learning the structured details and recovering the latent clean image together, from the shared information between the corrupted image and the latent image. In addition, instead of learning the pure difference (corruption), we propose to add a 'residual formatting layer' to format the residual to …

Editable View Optimized Tone Mapping For Viewing High Dynamic Range Panoramas On Head Mounted Display, Yuan Li

Boise State University Theses and Dissertations

Head mounted displays are characterized by relatively low resolution and low dynamic range. These limitations significantly reduce the visual quality of photo-realistic captures on such displays. This thesis presents an interactive view optimized tone mapping technique for viewing large sized high dynamic range panoramas up to 16384 by 8192 on head mounted displays. This technique generates a separate file storing pre-computed view-adjusted mapping function parameters. We define this technique as ToneTexture. The use of a view adjusted tone mapping allows for expansion of the perceived color space available to the end user. This yields an improved visual appearance of …

Object Detection Meets Knowledge Graphs, Yuan Fang, Kingsley Kuan, Jie Lin, Cheston Tan, Vijay Chandrasekhar

Research Collection School Of Computing and Information Systems

Object detection in images is a crucial task in computer vision, with important applications ranging from security surveillance to autonomous vehicles. Existing state-of-the-art algorithms, including deep neural networks, only focus on utilizing features within an image itself, largely neglecting the vast amount of background knowledge about the real world. In this paper, we propose a novel framework of knowledge-aware object detection, which enables the integration of external knowledge such as knowledge graphs into any object detection algorithm. The framework employs the notion of semantic consistency to quantify and generalize knowledge, which improves object detection through a re-optimization process to achieve …