Graphics and Human Computer Interfaces Commons^™

E-Classroom For An Underserved Institution, Bhanuprakash Madupati, Kaleem Danish Mohammed, Dilipkumar Pampana

All Capstone Projects

The E-Class Room system is a web based project. An educational institution in India is understaffed and has limited interaction among faculty, student and industry experts. The project is to provide an online platform for the students and faculty of the institution to enhance their educational needs and to share their learning with their fellow students, faculty or industrial experts. It aims to provide a platform for mutual cooperation between different kinds of learning. The new system will provide directional way for online learning between faculty, student and industrial experts.

Sense Beyond Expressions: Cuteness, Kang Wang, Tam Nguyen, Jiashi Feng, Jose Sepulveda

Computer Science Faculty Publications

With the development of Internet culture, cute has become a popular concept. Many people are curious about what factors making a person look cute. However, there is rare research to answer this interesting question. In this work, we construct a dataset of personal images with comprehensively annotated cuteness scores and facial attributes to investigate this high-level concept in depth. Based on this dataset, through an automatic attributes mining process, we find several critical attributes determining the cuteness of a person.

We also develop a novel Continuous Latent Support Vector Machine (C-LSVM) method to predict the cuteness score of one person …

Adaptive Nonparametric Image Parsing, Tam Nguyen, Canyi Lu, Jose Sepulveda, Shuicheng Yan

Computer Science Faculty Publications

In this paper, we present an adaptive nonparametric solution to the image parsing task, namely, annotating each image pixel with its corresponding category label. For a given test image, first, a locality-aware retrieval set is extracted from the training data based on superpixel matching similarities, which are augmented with feature extraction for better differentiation of local superpixels. Then, the category of each superpixel is initialized by the majority vote of the k -nearest-neighbor superpixels in the retrieval set. Instead of fixing k as in traditional nonparametric approaches, here, we propose a novel adaptive nonparametric approach that determines the sample-specific k …

Face Recognition On Large-Scale Video In The Wild With Hybrid Euclidean-And-Riemannian Metric Learning, Zhiwu Huang, R. Wang, S. Shan, X Chen

Research Collection School Of Computing and Information Systems

Face recognition on large-scale video in the wild is becoming increasingly important due to the ubiquity of video data captured by surveillance cameras, handheld devices, Internet uploads, and other sources. By treating each video as one image set, set-based methods recently have made great success in the field of video-based face recognition. In the wild world, videos often contain extremely complex data variations and thus pose a big challenge of set modeling for set-based methods. In this paper, we propose a novel Hybrid Euclidean-and-Riemannian Metric Learning (HERML) method to fuse multiple statistics of image set. Specifically, we represent each image …

A-Maze-D: Advanced Maze Development Kit Using Constraint Databases, Shruti Daggumarti, Peter Revesz, Corey Svehla

School of Computing: Conference and Workshop Papers

In this paper, we describe the A-Maze-D system which shows that constraint databases can be applied conveniently and efficiently to the design of maze games. A-Maze-D provides a versatile set of features by a combination of a MATLAB library and the MLPQ constraint database system. A-Maze-D is the first system that uses constraint databases to build maze games and opens new ideas in video game development.

Using Eye And Head Movements As A Control Mechanism For Tele-Operating A Ground-Based Robot And Its Payload, Kathryn C. Hicks

Computational Modeling & Simulation Engineering Theses & Dissertations

To date, eye and head tracking has been used to indicate users' attention patterns while performing a task or as an aid for disabled persons, to allow hands-free interaction with a computer. The increasing accuracy and the reduced cost of eye- and head-tracking equipment make utilizing this technology feasible for explicit control tasks, especially in cases where there is confluence between the visual task and control.

The goal of this research was to investigate the use of eye-tracking as a more natural interface for the control of a camera-equipped, remotely operated robot in tasks that require the operator to simultaneously …

Infotainment Interface Design For Automobiles, Ian R. Buck

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

In an increasingly connected, mobile world, situations where users do not interact with their digital lives are becoming few and far between. This can be a problem in situations that demand a user's attention for their safety. Driving is one such situation, and it is doubly important because a significant portion of the western population drives on a daily basis. Researchers have tested different interface designs with the goal of finding one that demands the least cognitive load while still allowing the user to perform the desired task efficiently. In this paper interfaces incorporating auditory cues, voice dictation, and air …

Rfid Microscope Lab, Patricia Carranza

Computer Engineering

The RFID Microscope Lab is a new exhibit created for the San Luis Obispo Children's Museum. The goal of the project is to create a modern, interactive exhibit that will teach children about different natural specimens through the use of technology. A computer, custom software, and RFID technology, will be used to display facts, microscopic images, and short videos of ten different specimens.

An Interactive User Interface Improves Data Visualization In R, Nathan Sweem

STAR Program Research Presentations

An interactive user interface application was created using the R statistical computing environment and the Shiny package to visualize historical data on the performance of mutual funds and exchange-traded funds (ETFs). Historical data for these funds is scraped from the Yahoo! Finance webpage. The application allows the user to analyze this historical data by category and fund family, which are also scraped from Yahoo! Finance. The application generates interactive plots to compare the performance of selected mutual funds and ETFs given the baseline and center determined by the user. The application has been modified to attentively match the data with …

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 …

Topological Spatial Verification For Instance Search, Wei Zhang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes an elastic spatial verification method for Instance Search, particularly for dealing with non-planar and non-rigid queries exhibiting complex spatial transformations. Different from existing models that map keypoints between images based on a linear transformation (e.g., affine, homography), our model exploits the topological arrangement of keypoints to address the non-linear spatial transformations that are extremely common in real life situations. In particular, we propose a novel technique to elastically verify the topological spatial consistency with the triangulated graph through a "sketch-and-match" scheme. The spatial topology configuration, emphasizing relative positioning rather than absolute coordinates, is first sketched by a …

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 …

Effects Of The Use Of Points, Leaderboards And Badges On In-Game Purchases Of Virtual Goods, Fiona Fui-Hoon Nah, Lakshmi Sushma Daggubati, Amith Tarigonda, Raghu Vinay Nuvvula, Ofir Turel

Research Collection School Of Computing and Information Systems

Game design elements are major factors in gamification. In this study, we seek to examine the impact of game design elements on users’ in-game purchases of virtual goods. The purchase of virtual goods due to players’ intrinsic motivation has been studied but little is known about the purchase of virtual goods due to the use of game design elements (i.e., Points, Leaderboards and Badges) built into the games. Extending our knowledge to this realm can help researchers to better understand gamers’ behaviors, and game designers and marketers to better promote and sell virtual goods in online games.

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.

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 …