Graphics and Human Computer Interfaces Commons^™

Applying Geocaching Principles To Site-Based Citizen Science And Eliciting Reactions Via A Technology Probe, Matthew A. Dunlap, Anthony Tang, Saul Greenberg

Research Collection School Of Computing and Information Systems

Site-based citizen science occurs when volunteers work with scientists to collect data at particular field locations. The benefit is greater data collection at lesser cost. Yet difficulties exist. We developed SCIENCECACHING, a prototype citizen science aid designed to mitigate four specific problems by applying aspects from another thriving location-based activity: geocaching as enabled by mobile devices. Specifically, to ease problems in data collection, SCIENCECACHING treats sites as geocaches: Volunteers find sites opportunistically via geocaching methods and use equipment and other materials pre-stored in cache containers. To ease problems in data validation, SCIENCECACHING flags outlier data as it is entered so …

Creating Greater Synergy Between Hci Academia And Practice, Fiona Fui-Hoon Nah, Dennis Galletta, Melinda Knight, James R. Lewis, John Pruitt, Gavriel Salvendy, Hong Sheng, Anna Wichansky

Research Collection School Of Computing and Information Systems

This paper presents perspectives from both academia and practice on how both groups can collaborate and work together to create synergy in the development and advancement of human-computer interaction (HCI). Issues and challenges are highlighted, success cases are offered as examples, and suggestions are provided to further such collaborations.

Semi-Supervised Hashing With Semantic Confidence For Large Scale Visual Search, Yingwei Pan, Ting Yao, Houqiang Li, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

Similarity search is one of the fundamental problems for large scale multimedia applications. Hashing techniques, as one popular strategy, have been intensively investigated owing to the speed and memory efficiency. Recent research has shown that leveraging supervised information can lead to high quality hashing. However, most existing supervised methods learn hashing function by treating each training example equally while ignoring the different semantic degree related to the label, i.e. semantic confidence, of different examples. In this paper, we propose a novel semi-supervised hashing framework by leveraging semantic confidence. Specifically, a confidence factor is first assigned to each example by neighbor …

Teaching Big Data By Three Levels Of Projects, Jianjun Yang, Ju Shen

Computer Science Faculty Publications

Big Data is a new topic and it is very hot nowadays. However, it is difficult to teach Big Data effectively by regular lecture. In this paper, we present a unique way to teach students Big Data by developing three levels of projects from easy to difficult. The three levels projects are initializing project, designing project, and comprehensive projects. They are developed to involve students in Big Data, train students' skills to analyze concrete problems of Big Data, and develop students' creative abilities and their abilities to solve real setting problems.

On Multipath Link Characterization And Adaptation For Device-Free Human Detection, Zimu Zhou, Zheng Yang, Chenshu Wu, Yunhao Liu, Lionel M. Ni

Research Collection School Of Computing and Information Systems

No abstract provided.

State Preserving Extreme Learning Machine For Face Recognition, Md. Zahangir Alom, Paheding Sidike, Vijayan K. Asari, Tarek M. Taha

Electrical and Computer Engineering Faculty Publications

Extreme Learning Machine (ELM) has been introduced as a new algorithm for training single hidden layer feed-forward neural networks (SLFNs) instead of the classical gradient-based algorithms. Based on the consistency property of data, which enforce similar samples to share similar properties, ELM is a biologically inspired learning algorithm with SLFNs that learns much faster with good generalization and performs well in classification applications. However, the random generation of the weight matrix in current ELM based techniques leads to the possibility of unstable outputs in the learning and testing phases. Therefore, we present a novel approach for computing the weight matrix …

Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-Ching S. Cheung, Rita Patel

Computer Science Faculty Publications

Video self modeling (VSM) is a behavioral intervention technique in which a learner models a target behavior by watching a video of him- or herself. In the field of speech language pathology, the approach of VSM has been successfully used for treatment of language in children with Autism and in individuals with fluency disorder of stuttering. Technical challenges remain in creating VSM contents that depict previously unseen behaviors. In this paper, we propose a novel system that synthesizes new video sequences for VSM treatment of patients with voice disorders. Starting with a video recording of a voice-disorder patient, the proposed …

Salient Object Detection Via Augmented Hypotheses, Tam Nguyen, Jose Sepulveda

Computer Science Faculty Publications

In this paper, we propose using augmented hypotheses which consider objectness, foreground, and compactness for salient object detection. Our algorithm consists of four basic steps. First, our method generates the objectness map via objectness hypotheses. Based on the objectness map, we estimate the foreground margin and compute the corresponding foreground map which prefers the foreground objects. From the objectness map and the foreground map, the compactness map is formed to favor the compact objects. We then derive a saliency measure that produces a pixel-accurate saliency map which uniformly covers the objects of interest and consistently separates foreground and background.

We …

Between Worlds: Securing Mixed Javascript/Actionscript Multi-Party Web Content, Phu Huu Phung, Maliheh Monshizadeh, Meera Sridhar, Kevin W. Hamlen, V. N. Venkatakrishnan

Computer Science Faculty Publications

Mixed Flash and JavaScript content has become increasingly prevalent; its purveyance of dynamic features unique to each platform has popularized it for myriad Web development projects. Although Flash and JavaScript security has been examined extensively, the security of untrusted content that combines both has received considerably less attention. This article considers this fusion in detail, outlining several practical scenarios that threaten the security of Web applications. The severity of these attacks warrants the development of new techniques that address the security of Flash-JavaScript content considered as a whole, in contrast to prior solutions that have examined Flash or JavaScript security …

Log-Euclidean Metric Learning On Symmetric Positive Definite Manifold With Application To Image Set Classification, Zhiwu Huang, R. Wang, S. Shan, X. Li, X. Chen

Research Collection School Of Computing and Information Systems

The manifold of Symmetric Positive Definite (SPD) matrices has been successfully used for data representation in image set classification. By endowing the SPD manifold with Log-Euclidean Metric, existing methods typically work on vector-forms of SPD matrix logarithms. This however not only inevitably distorts the geometrical structure of the space of SPD matrix logarithms but also brings low efficiency especially when the dimensionality of SPD matrix is high. To overcome this limitation, we propose a novel metric learning approach to work directly on logarithms of SPD matrices. Specifically, our method aims to learn a tangent map that can directly transform the …

Automatic User Profile Construction For A Personalized News Recommender System Using Twitter, Shiva Theja Reddy Gopidi

Graduate Theses and Dissertations

Modern society has now grown accustomed to reading online or digital news. However, the huge corpus of information available online poses a challenge to users when trying to find relevant articles. A hybrid system “Personalized News Recommender Using Twitter’ has been developed to recommend articles to a user based on the popularity of the articles and also the profile of the user. The hybrid system is a fusion of a collaborative recommender system developed using tweets from the “Twitter” public timeline and a content recommender system based the user’s past interests summarized in their conceptual user profile. In previous work, …

Supporting Adult Learners' Metacognitive Development With A Sociotechnical System, Kathryn Wozniak

College of Computing and Digital Media Dissertations

Metacognition is defined as thinking about and reflecting on one's cognitive processes. In learning contexts, strong metacognition leads to retention, academic success, and deep learning. While we know a lot about the metacognition of learners in grades K-12 and college, there are limited studies on adult learners' (24 and older) metacognitive awareness, how to support it, or the role technology can play, particularly since e-learning is quickly becoming the central mode of learning for adult learners. Thus, I have the following motivating research question: How can we support adult learners' metacognitive development in e-learning environments?

To better understand adult learners' …

Dynamic Voxel Based Terrain Generation, Thomas Sanford

Computer Science and Software Engineering

This project is an implementation of an editable terrain system. By maintaining an octree of volumetric data and performing the mesh creation on the GPU, the program can allow for free editing of the surroundings which is then reflected in real time. This allows for real time applications to have terrain that can change depending on how the user interacts with it.

Multiplayer Browser-Based Game Utilizing Javascript And Webgl Frameworks, Cy Tan, Benjamin Naftali, Matthew Tong, Vincent Chan

Computer Science and Software Engineering

The goal of our project is to make an online large-scale multiplayer game with persistent user data. This will involve real-time player interaction and many customization options. This game will be a massively-multiplayer online tactics role-playing game (MMOTRPG), a genre that has been insufficiently explored. This area of browser-based massive multiplayer games is also a platform of gaming that has yet to realize the capabilities of modern browsers and the level of interaction and graphics they now support.

The scope of our project does not encompass the complete feature set we have intended for the game, but rather a technical …

'Fo Fighter: 2d Real-Time Game, Cary Dobeck

Computer Engineering

‘FO Fighter is a 2D real-time game for Android and iOS mobile devices. The game utilizes the motion sensors and touch screens built within these devices to give the player a great amount of control over their character’s position and firing direction. This control allows for a reactive environment set in outer space, where gravity is determined by the device’s orientation, while the player must dodge, fight and destroy multiple enemy fighters on each planet in the solar system. ‘FO Fighter has been tested throughout its development cycle on numerous devices on both the Android and iOS platforms, with testers …

Moxel Dags: Connecting Material Information To High Resolution Sparse Voxel Dags, Brent Robert Williams

Master's Theses

As time goes on, the demand for higher resolution and more visually rich images only increases. Unfortunately, creating these more realistic computer graphics is pushing our computational resources to their limits.

In realistic rendering, one of the common ways 3D objects are represented is as volumetric elements called voxels. Traditionally, voxel data structures are known for their high memory requirements. One of the standard ways these requirements are minimized is by storing the voxels in a sparse voxel octree (SVO). Very recently, a method called High Resolution Sparse Voxel DAGs was presented that can store binary voxel data orders of …

Brain Machine Interface Using Emotiv Epoc To Control Robai Cyton Robotic Arm, Daniel P. Prince, Mark J. Edmonds, Andrew J. Sutter, Matthew Thomas Cusumano, Wenjie Lu, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

The initial framework for an electroencephalography (EEG) thought recognition software suite is developed, built, and tested. This suite is designed to recognize human thoughts and pair them to actions for controlling a robotic arm.

Raw EEG brain activity data is collected using an Emotiv EPOC headset. The EEG data is processed through linear discriminant analysis (LDA), where an intended action is identified. The EEG classification suite is being developed to increase the number of distinct actions that can be identified compared to the Emotiv recognition software. The EEG classifier was able to correctly distinguish between two separate physical movements.

Future …

Online Multimodal Co-Indexing And Retrieval Of Weakly Labeled Web Image Collections, Lei Meng, Ah-Hwee Tan, Cyril Leung, Liqiang Nie, Tan-Seng Chua, Chunyan Miao

Research Collection School Of Computing and Information Systems

Weak supervisory information of web images, such as captions, tags, and descriptions, make it possible to better understand images at the semantic level. In this paper, we propose a novel online multimodal co-indexing algorithm based on Adaptive Resonance Theory, named OMC-ART, for the automatic co-indexing and retrieval of images using their multimodal information. Compared with existing studies, OMC-ART has several distinct characteristics. First, OMCART is able to perform online learning of sequential data. Second, OMC-ART builds a two-layer indexing structure, in which the first layer co-indexes the images by the key visual and textual features based on the generalized distributions …

Unsupervised Celebrity Face Naming In Web Videos, Lei Pang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper investigates the problem of celebrity face naming in unconstrained videos with user-provided metadata. Instead of relying on accurate face labels for supervised learning, a rich set of relationships automatically derived from video content and knowledge from image domain and social cues is leveraged for unsupervised face labeling. The relationships refer to the appearances of faces under different spatio-temporal contexts and their visual similarities. The knowledge includes Web images weakly tagged with celebrity names and the celebrity social networks. The relationships and knowledge are elegantly encoded using conditional random field (CRF) for label inference. Two versions of face annotation …

Improving Automatic Name-Face Association Using Celebrity Images On The Web, Zhineng Chen, Bailan Feng, Chong-Wah Ngo, Caiyan Jia, Xiangsheng Huang

Research Collection School Of Computing and Information Systems

This paper investigates the task of automatically associating faces appearing in images (or videos) with their names. Our novelty lies in the use of celebrity Web images to facilitate the task. Specifically, we first propose a method named Image Matching (IM), which uses the faces in images returned from name queries over an image search engine as the gallery set of the names, and a probe face is classified as one of the names, or none of them, according to their matching scores and compatibility characterized by a proposed Assigning-Thresholding (AT) pipeline. Noting IM could provide guidance for association for …

Multimodal Learning With Deep Boltzmann Machine For Emotion Prediction In User Generated Videos, Lei Pang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Detecting emotions from user-generated videos, such as“anger” and “sadness”, has attracted widespread interest recently. The problem is challenging as effectively representing video data with multi-view information (e.g., audio, video or text) is not trivial. In contrast to the existing works that extract features from each modality (view) separately followed by early or late fusion, we propose to learn a joint density model over the space of multi-modal inputs (including visual, auditory and textual modalities) with Deep Boltzmann Machine (DBM). The model is trained directly on the user-generated Web videos without any labeling effort. More importantly, the deep architecture enlightens the …

Drill Design Suite, Neil Nordhof

Computer Science and Software Engineering

Drill Design Suite is a lightweight tool for creating drill for marching band programs.

Face Video Retrieval With Image Query Via Hashing Across Euclidean Space And Riemannian Manifold, Y. Li, R. Wang, Zhiwu Huang, S. Shan, X. Chen

Research Collection School Of Computing and Information Systems

Retrieving videos of a specific person given his/her face image as query becomes more and more appealing for applications like smart movie fast-forwards and suspect searching. It also forms an interesting but challenging computer vision task, as the visual data to match, i.e., still image and video clip are usually represented quite differently. Typically, face image is represented as point (i.e., vector) in Euclidean space, while video clip is seemingly modeled as a point (e.g., covariance matrix) on some particular Riemannian manifold in the light of its recent promising success. It thus incurs a new hashing-based retrieval problem of matching …

Projection Metric Learning On Grassmann Manifold With Application To Video Based Face Recognition, Zhiwu Huang, R. Wang, S. Shan, X. Chen

Research Collection School Of Computing and Information Systems

In video based face recognition, great success has been made by representing videos as linear subspaces, which typically lie in a special type of non-Euclidean space known as Grassmann manifold. To leverage the kernel-based methods developed for Euclidean space, several recent methods have been proposed to embed the Grassmann manifold into a high dimensional Hilbert space by exploiting the well established Project Metric, which can approximate the Riemannian geometry of Grassmann manifold. Nevertheless, they inevitably introduce the drawbacks from traditional kernel-based methods such as implicit map and high computational cost to the Grassmann manifold. To overcome such limitations, we propose …

Semi-Supervised Domain Adaptation With Subspace Learning For Visual Recognition, Ting Yao, Yingwei Pan, Chong-Wah Ngo, Houqiang Li, Tao Mei

Research Collection School Of Computing and Information Systems

In many real-world applications, we are often facing the problem of cross domain learning, i.e., to borrow the labeled data or transfer the already learnt knowledge from a source domain to a target domain. However, simply applying existing source data or knowledge may even hurt the performance, especially when the data distribution in the source and target domain is quite different, or there are very few labeled data available in the target domain. This paper proposes a novel domain adaptation framework, named Semi-supervised Domain Adaptation with Subspace Learning (SDASL), which jointly explores invariant lowdimensional structures across domains to correct data …

Non-Orientable Objects As Gaming Surfaces, Haley P. Bourke, Paul Latiolais

Student Research Symposium

Developed in Python, Klein Space Fighter is an interactive learning tool and mathematically themed arcade game that allows the player to combat on different mathematical surfaces including a 2D Klein bottle. The app is available for Android and desktop devices, and will be made available for iOS in the future.

To receive an invitation to download the app through Google Play, contact me at [email protected]

Compression Of Video Tracking And Bandwidth Balancing Routing In Wireless Multimedia Sensor Networks, Yin Wang, Jianjun Yang, Ju Shen, Bryson Payne, Juan Guo, Kun Hua

Computer Science Faculty Publications

There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select …

Design, Programming, And User-Experience, Kaila G. Manca

Honors Scholar Theses

This thesis is a culmination of my individualized major in Human-Computer Interaction. As such, it showcases my knowledge of design, computer engineering, user-experience research, and puts into practice my background in psychology, com- munications, and neuroscience.

I provided full-service design and development for a web application to be used by the Digital Media and Design Department and their students.This process involved several iterations of user-experience research, testing, concepting, branding and strategy, ideation, and design. It lead to two products.

The first product is full-scale development and optimization of the web appli- cation.The web application adheres to best practices. It was …

Development Of A Tridimensional Measuring Application For Ipads, Michael Casebolt, Nicolas Kouatli, Jack Mullen

Computer Science and Software Engineering

In today’s fast-paced distribution centers workers and management alike are constantly searching for the quickest and most efficient way to package items for distribution. Even with the advancement of app-oriented solutions to a variety of problems across many industries there is a distinct unmet need in distribution environments for an application capable of increasing the efficiency and accuracy of packaging items. This senior project focused on the development and testing of an application utilizing the Structure Three Dimensional Sensor and a 4th generation iPad to scan an object or group of objects to be packaged and determine the overall dimensions …

Interpretation At The Controller's Edge: The Role Of Graphical User Interfaces In Virtual Archaeology, Tyler Duane Johnson

Graduate Theses and Dissertations

The important role of graphical user interfaces (GUIs) as a medium of interaction with technology is well established in the world of media design, but has not received significant attention in the field of virtual archaeology. GUIs provide interactive capabilities and contextual information for 3D content such as structure-from-motion (SFM) models, and can represent the difference between "raw data" and thoughtful, skilled scholarly publications. This project explores the implications of a GUI created with the game engine Unity 3D (Unity) for a series of SFM models recorded at a structure known as the Area B House at the ancient central …