Graphics and Human Computer Interfaces Commons^™

A Content-Sensitive Wiki Help System, Eswara Satya Pavan Rajesh Pinapala

Master's Projects

Context-sensitive help is a software application component that enables users to open help pertaining to their state, location, or the action they are performing within the software. Context-sensitive “wiki” help, on the other hand, is help powered by a wiki system with all the features of context-sensitive help. A context-sensitive wiki help system aims to make the context-sensitive help collaborative; in addition to seeking help, users can directly contribute to the help system. I have implemented a context-sensitive wiki help system into Yioop, an open source search engine and software portal created by Dr. Chris Pollett, in order to measure …

The Effects Of Gamifying Optional Lessons On Motivation, Aaron Zemach

McKelvey School of Engineering Graduate Student Theses & Dissertations

Adding video-game elements to non-video-game interfaces (“gamification”) has become a common engagement strategy over the past several years in the domain of education. While prior studies have found that adding game elements to mandatory educational materials can increase students’ motivation to complete the materials, there has yet to be a study to investigate if game elements can make users more likely to engage with optional educational materials. In this study, we investigate whether users of a gamified educational interface are more motivated than users of a non-gamified interface to voluntarily complete educational materials. We found users of a gamified interface …

A Function-To-Task Process Model For Adaptive Automation System Design, Jason M. Bindewald, Michael E. Miller, Gilbert L. Peterson

Faculty Publications

Adaptive automation systems allow the user to complete a task seamlessly with a computer performing tasks at which the human operator struggles. Unlike traditional systems that allocate functions to either the human or the machine, adaptive automation varies the allocation of functions during system operation. Creating these systems requires designers to consider issues not present during static system development. To assist in adaptive automation system design, this paper presents the concept of inherent tasks and takes advantage of this concept to create the function-to-task design process model. This process model helps the designer determine how to allocate functions to the …

Is The Smartphone Smart In Kathmandu?, Seth Bird

Independent Study Project (ISP) Collection

This is the extensive study of the smartphone in the developing country of Nepal, specifically the Kathmandu valley. Throughout my research I conducted various interviews with businesses, Tibetan refugees, and Nepali millennials (18yrs-33yrs) with the goal of identifying how the smartphone is used and understood. I chose the Kathmandu valley as my main area of research because the usage of smartphones in rural Nepal is extremely limited, and the valley represents the economic hub where progressive thinking flourishes. As a main objective I sought to understand how, if at all, the smartphone is used differently between Nepal and America. All …

Designing A Bayer Filter With Smooth Hue Transition Interpolation Using The Xilinx System Generator, Zhiqiang Li, Peter Revesz

School of Computing: Conference and Workshop Papers

This paper describes the design of a Bayer filter with smooth hue transition using the System Generator for DSP. We describe and compare experimentally two different designs, one based on a MATLAB implementation and the other based on a modification of the Bayer filter using bilinear interpolation.

Click-Through-Based Subspace Learning For Image Search, Yingwei Pan, Ting Yao, Xinmei Tian, Houqiang Li, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

One of the fundamental problems in image search is to rank image documents according to a given textual query. We address two limitations of the existing image search engines in this paper. First, there is no straightforward way of comparing textual keywords with visual image content. Image search engines therefore highly depend on the surrounding texts, which are often noisy or too few to accurately describe the image content. Second, ranking functions are trained on query-image pairs labeled by human labelers, making the annotation intellectually expensive and thus cannot be scaled up. We demonstrate that the above two fundamental challenges …

Imagespirit: Verbal Guided Image Parsing, Ming-Ming Cheng, Shuai Zheng, Wen-Yan Lin, Vibhav Vineet, Paul Sturgess, Nigel Crook, Niloy J. Mitra, Philip Torr

Research Collection School Of Computing and Information Systems

Humans describe images in terms of nouns and adjectives while algorithms operate on images represented as sets of pixels. Bridging this gap between how humans would like to access images versus their typical representation is the goal of image parsing, which involves assigning object and attribute labels to pixels. In this article we propose treating nouns as object labels and adjectives as visual attribute labels. This allows us to formulate the image parsing problem as one of jointly estimating per-pixel object and attribute labels from a set of training images. We propose an efficient (interactive time) solution. Using the extracted …

Celelabel: An Interactive System For Annotating Celebrities In Web Videos, Zhineng Chen, Jinfeng Bai, Chong-Wah Ngo, Bailan Feng, Bo Xu

Research Collection School Of Computing and Information Systems

Manual annotation of celebrities in Web videos is an essential task in many people-related Web services. The task, however, poses a significant challenge even to skillful annotators, mainly due to the large quantity of unfamiliar and greatly varied celebrities, and the lack of a customized system for it. This work develops CeleLabel, an interactive system for manually annotating celebrities in the Web video domain. The peculiarity of CeleLabel is to exploit and display multiple types of information that could assist the annotation, including video content, context surrounding and within a video, celebrity images on the Web, and human factors. Using …

Scalable Visual Instance Mining With Threads Of Features, Wei Zhang, Hongzhi Li, Chong-Wah Ngo, Shih-Fu Chang

Research Collection School Of Computing and Information Systems

We address the problem of visual instance mining, which is to extract frequently appearing visual instances automatically from a multimedia collection. We propose a scalable mining method by exploiting Thread of Features (ToF). Specifically, ToF, a compact representation that links consistent features across images, is extracted to reduce noises, discover patterns, and speed up processing. Various instances, especially small ones, can be discovered by exploiting correlated ToFs. Our approach is significantly more effective than other methods in mining small instances. At the same time, it is also more efficient by requiring much fewer hash tables. We compared with several state-of-the-art …

Vireo @ Trecvid 2014: Instance Search And Semantic Indexing, Wei Zhang, Hao Zhang, Ting Yao, Yijie Lu, Jingjing Chen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper summarizes the following two tasks participated by VIREO group: instance search and semantic indexing. We will present our approaches and analyze the results obtained in TRECVID 2014 benchmark evaluation

Combining Multiple Kernel Methods On Riemannian Manifold For Emotion Recognition In The Wild, M. Liu, R. Wang, S. Li, S. Shan, Zhiwu Huang, X. Chen

Research Collection School Of Computing and Information Systems

In this paper, we present the method for our submission to the Emotion Recognition in the Wild Challenge (EmotiW 2014). The challenge is to automatically classify the emotions acted by human subjects in video clips under realworld environment. In our method, each video clip can be represented by three types of image set models (i.e. linear subspace, covariance matrix, and Gaussian distribution) respectively, which can all be viewed as points residing on some Riemannian manifolds. Then different Riemannian kernels are employed on these set models correspondingly for similarity/distance measurement. For classification, three types of classifiers, i.e. kernel SVM, logistic regression, …

Hybrid Euclidean-And-Riemannian Metric Learning For Image Set Classification, Zhiwu Huang, R. Wang, S. Shan, X. Chen

Research Collection School Of Computing and Information Systems

We propose a novel hybrid metric learning approach to combine multiple heterogenous statistics for robust image set classification. Specifically, we represent each set with multiple statistics – mean, covariance matrix and Gaussian distribution, which generally complement each other for set modeling. However, it is not trivial to fuse them since the mean vector with dd-dimension often lies in Euclidean space RdRd, whereas the covariance matrix typically resides on Riemannian manifold Sym+dSymd+. Besides, according to information geometry, the space of Gaussian distribution can be embedded into another Riemannian manifold Sym+d+1Symd+1+. To fuse these statistics from heterogeneous spaces, we propose a Hybrid …

Organizing Video Search Results To Adapted Semantic Hierarchies For Topic-Based Browsing, Jiajun Wang, Yu-Gang Jiang, Qiang Wang, Kuiyuan Yang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Organizing video search results into semantically structured hierarchies can greatly improve the efficiency of browsing complex query topics. Traditional hierarchical clustering techniques are inadequate since they lack the ability to generate semantically interpretable structures. In this paper, we introduce an approach to organize video search results to an adapted semantic hierarchy. As many hot search topics such as celebrities and famous cities have Wikipedia pages where hierarchical topic structures are available, we start from the Wikipedia hierarchies and adjust the structures according to the characteristics of the returned videos from a search engine. Ordinary clustering based on textual information of …

Vireo-Tno @ Trecvid 2014: Multimedia Event Detection And Recounting (Med And Mer), Chong-Wah Ngo, Yi-Jie Lu, Hao Zhang, Ting Yao, Chun-Chet Tan, Lei Pang, Maaike De Boer, John Schavemaker, Klamer Schutte, Wessel Kraaij

Research Collection School Of Computing and Information Systems

This paper presents an overview and comparative analysis of our systems designed for TRECVID 2014 [1] multimedia event detection (MED) and recounting (MER) tasks, including all sub-tasks for Pre-Specified (PS) event detection, all sub-tasks except 100Ex for Ad-Hoc (AH) event detection, and 010Ex sub-task for both PS and AH event recounting. Multimedia Event Detection (MED) : Our main focus for the MED task is on the study of a new zero-example system, which aims to solve the 000Ex and SQ problems. The system can run either fully automatically or semi-automatically. Specifically, we test the automatic run in 000Ex submission and …

Taming The Software Chaos: True To Its Promise, Iftdss Eases The Burden Of Fuels Treatment Planning—And Does A Lot More Besides, Gail Wells

Joint Fire Science Program Digests

A key problem reported by the fuels treatment planning community is the difficulty and inefficiency of evaluating and then applying many planning tools and applications. Fuels specialists have struggled to find, load, and learn all the different fuels and fire planning models, not to mention the interface of running, adjusting, and inputting data specific to each model without the ability to easily share inputs/outputs between models.

The Interagency Fuels Treatment Decision Support System (IFTDSS) was conceived as a way for users to learn one interface, access a variety of data and models all in one place, and pass data (inputs …

Designing An Immersive And Entertaining Pervasive Gameplay Experience With Spheros As Game And Interface Elements, Brennan Jones, Kody Dillman, Setareh Aghel Manesh, Ehud Sharlin, Anthony Tang

Research Collection School Of Computing and Information Systems

The Sphero is a robotic remote-controlled ball capable of rolling around on its own in any direction at multiple speeds. Numerous games have been designed for the Sphero for smartphones and tablets. However, most of these games provide an interface for controlling the Sphero that is far from natural. These games also do not put a strong focus on the physical environment around the Sphero. This work discusses a control scheme used to control a Sphero with another Sphero, and a pervasive game leveraging this scheme that emphasizes physical properties of the environment to create an immersive experience.

Personality Profiles Of Software Engineers And Their Software Quality Preferences, Arif Raza, Luiz Fernando Capretz, Zaka Ul-Mustafa

Electrical and Computer Engineering Publications

Studies related to human aspects in software engineering (SE) have been performed from different perspectives. These perspectives include the study of human factors in different phases of software life cycle, effect of team performance in software development, how can a personality trait suit a particular task, and about some other miscellaneous issues. This research work aims to establish personality profiles of Pakistani software engineers using the Myers-Briggs Type Indicator (MBTI) instrument. In this survey, we have collected personality profiles of 110 software engineers. Moreover, their preferences of software quality attributes have also been collected. Analysis of the study shows that …

Seeing Human Weight From A Single Rgb-D Image, Tam Nguyen, Jiashi Feng, Shuicheng Yan

Computer Science Faculty Publications

Human weight estimation is useful in a variety of potential applications, e.g., targeted advertisement, entertainment scenarios and forensic science. However, estimating weight only from color cues is particularly challenging since these cues are quite sensitive to lighting and imaging conditions. In this article, we propose a novel weight estimator based on a single RGB-D image, which utilizes the visual color cues and depth information. Our main contributions are three-fold.

First, we construct the W8-RGBD dataset including RGB-D images of different people with ground truth weight.

Second, the novel sideview shape feature and the feature fusion model are proposed to facilitate …

Saliency Detection With Flash And No-Flash Image Pairs, Shengfeng He, Rynson W.H. Lau

Research Collection School Of Computing and Information Systems

In this paper, we propose a new saliency detection method using a pair of flash and no-flash images. Our approach is inspired by two observations. First, only the foreground objects are significantly brightened by the flash as they are relatively nearer to the camera than the background. Second, the brightness variations introduced by the flash provide hints to surface orientation changes. Accordingly, the first observation is explored to form the background prior to eliminate background distraction. The second observation provides a new orientation cue to compute surface orientation contrast. These photometric cues from the two observations are independent of visual …

Name-Face Association In Web Videos: A Large-Scale Dataset, Baselines, And Open Issues, Zhi-Neng Chen, Chong-Wah Ngo, Wei Zhang, Juan Cao, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Associating faces appearing in Web videos with names presented in the surrounding context is an important task in many applications. However, the problem is not well investigated particularly under large-scale realistic scenario, mainly due to the scarcity of dataset constructed in such circumstance. In this paper, we introduce a Web video dataset of celebrities, named WebV-Cele, for name-face association. The dataset consists of 75 073 Internet videos of over 4 000 hours, covering 2 427 celebrities and 649 001 faces. This is, to our knowledge, the most comprehensive dataset for this problem. We describe the details of dataset construction, discuss …

A Method To Develop Neck Injury Criteria To Aid Design And Test Of Escape Systems Incorporating Helmet Mounted Displays, Jeffrey C. Parr

Theses and Dissertations

HMDs are becoming common human-machine interface equipment in manned military flight, but introducing this equipment into the overall aircraft escape system poses new and significant system design, development, and test concerns. Although HMDs add capabilities, which improve operator performance, the increased capability is often accompanied by increased head supported mass. The increased mass can amplify the risk of pilot neck injury during ejection when compared to lighter legacy helmets. Currently no adequate USAF neck injury criteria exist to effectively guide the requirements, design, and test of escape systems for pilots with HMDs. This research effort presents a novel method to …

Wireless Location Determination: Using Existing 802.11 Wireless Networks To Determine A Users Location, Travis Calvert

Journal of Undergraduate Research at Minnesota State University, Mankato

The ability to determine a user’s location through an existing 802.11 wireless network has vast implications in the area of context-aware and pervasive computing. Such abilities have been developed mainly in the Linux environment to date. To maximize its usefulness, a location determination system was developed for the more dominant Windows operation system. While being able to operate outdoors as well as indoors, this system succeeds where traditional GPS (Global Positioning Systems) fail, namely indoor environments. This system could benefit the large number of existing wireless networks and requires no additional hardware; only a few simple software downloads. The ability …

Mental Health Awareness Building Via Android Application, James Faraday, Joshua Martin

Journal of Undergraduate Research at Minnesota State University, Mankato

The goal of this project was to create a tool that provides students at Minnesota State University, Mankato with mental health information through a freely available smartphone application (App). Our approach used a software engineering design process that focused on who our customers are, what resources are available, and how we can best connect the two to improve student lives. We identified the stakeholders involved and worked with campus mental health professionals to help shape our App. While there is a broad range of mental health topics, we have focused on materials related to depression. The first process of the …

Data Visualization To Evaluate And Facilitate Targeted Data Acquisitions In Support Of A Real-Time Ocean Forecasting System, Edward A. Holmberg Iv

LSU New Orleans Theses and Dissertations

A robust evaluation toolset has been designed for Naval Research Laboratory’s Real-Time Ocean Forecasting System RELO with the purpose of facilitating an adaptive sampling strategy and providing a more educated guidance for routing underwater gliders. The major challenges are to integrate into the existing operational system, and provide a bridge between the modeling and operative environments. Visualization is the selected approach and the developed software is divided into 3 packages: The first package is to verify that the glider is actually following the waypoints and to predict the position of the glider for the next cycle’s instructions. The second package …

Spatiotemporal Crime Analysis, James Q. Tay, Abish Malik, Sherry Towers, David Ebert

The Summer Undergraduate Research Fellowship (SURF) Symposium

There has been a rise in the use of visual analytic techniques to create interactive predictive environments in a range of different applications. These tools help the user sift through massive amounts of data, presenting most useful results in a visual context and enabling the person to rapidly form proactive strategies. In this paper, we present one such visual analytic environment that uses historical crime data to predict future occurrences of crimes, both geographically and temporally. Due to the complexity of this analysis, it is necessary to find an appropriate statistical method for correlative analysis of spatiotemporal data, as well …

An Adaptive Educational Game To Help Students Learn How To Solve Systems Of Linear Equations, Wang Zhang

Theses and Dissertations

Educational games have been proven to be effective in developing problem solving skills in well-defined domain, such as Math and Physics. In this thesis, an educational game called Matrix was developed to foster problem solving skills in the domain of linear algebra, particularly solving a system of linear equations. Matrix is an adaptive educational game that uses intelligent tutoring modules to guide the student's learning process and provide feedback based on the student's performance. These modules are domain module, student module, pedagogical module and presentation module. The domain module contains all the concepts the student needs to learn and an …

Video Event Detection Using Motion Relativity And Feature Selection, Feng Wang, Zhanhu Sun, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Event detection plays an essential role in video content analysis. In this paper, we present our approach based on motion relativity and feature selection for video event detection. First, we propose a new motion feature, namely Expanded Relative Motion Histogram of Bag-of-Visual-Words (ERMH-BoW) to employ motion relativity for event detection. In ERMH-BoW, by representing what aspect of an event with Bag-of-Visual-Words (BoW), we construct relative motion histograms between different visual words to depict the objects' activities or how aspect of the event. ERMH-BoW thus integrates both what and how aspects for a complete event description. Meanwhile, we show that by …

Structure Preserving Large Imagery Reconstruction, Ju Shen, Jianjun Yang, Sami Taha Abu Sneineh, Bryson Payne, Markus Hitz

Computer Science Faculty Publications

With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for various goals, such as image clustering, 3D scene reconstruction, and other big data applications. However, such tasks are not easy due to the fact the retrieved photos can have large variations in their view perspectives, resolutions, lighting, noises, and distortions. Furthermore, with the occlusion of unexpected objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image …

Click-Through-Based Cross-View Learning For Image Search, Yingwei Pan, Ting Yao, Tao Mei, Houqiang Li, Chong-Wah Ngo, Yong Rui

Research Collection School Of Computing and Information Systems

One of the fundamental problems in image search is to rank image documents according to a given textual query. Existing search engines highly depend on surrounding texts for ranking images, or leverage the query-image pairs annotated by human labelers to train a series of ranking functions. However, there are two major limitations: 1) the surrounding texts are often noisy or too few to accurately describe the image content, and 2) the human annotations are resourcefully expensive and thus cannot be scaled up. We demonstrate in this paper that the above two fundamental challenges can be mitigated by jointly exploring the …

Collaborative Error Reduction For Hierarchical Classification, Shiai Zhu, Xiao-Yong Wei, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Hierarchical classification (HC) is a popular and efficient way for detecting the semantic concepts from the images. The conventional method always selects the branch with the highest classification response. This branch selection strategy has a risk of propagating classification errors from higher levels of the hierarchy to the lower levels. We argue that the local strategy is too arbitrary, because the candidate nodes are considered individually, which ignores the semantic and context relationships among concepts. In this paper, we first propose a novel method for HC, which is able to utilize the semantic relationship among candidate nodes and their children …