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Visualization

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Articles 1 - 30 of 46

Full-Text Articles in Graphics and Human Computer Interfaces

Generalized Visual Relation Detection With Diffusion Models, Kaifeng Gao, Siqi Chen, Hanwang Zhang, Jun Xiao, Yueting Zhuang, Qianru Sun Jan 2026

Generalized Visual Relation Detection With Diffusion Models, Kaifeng Gao, Siqi Chen, Hanwang Zhang, Jun Xiao, Yueting Zhuang, Qianru Sun

Research Collection School Of Computing and Information Systems

Visual relation detection (VRD) aims to identify relationships (or interactions) between object pairs in an image. Although recent VRD models have achieved impressive performance, they are all restricted to pre-defined relation categories, while failing to consider the semantic ambiguity characteristic of visual relations. Unlike objects, the appearance of visual relations is always subtle and can be described by multiple predicate words from different perspectives, e.g., “ride” can be depicted as “race” and “sit on”, from the sports and spatial position views, respectively. To this end, we propose to model visual relations as continuous embeddings, and design diffusion models to achieve …

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Dreamanime: Learning Style-Identity Textual Disentanglement For Anime And Beyond, Chenshu Xu, Yangyang Xu, Huaidong Zhang, Xuemiao Xu, Shengfeng He Aug 2025

Dreamanime: Learning Style-Identity Textual Disentanglement For Anime And Beyond, Chenshu Xu, Yangyang Xu, Huaidong Zhang, Xuemiao Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

Text-to-image generation models have significantly broadened the horizons of creative expression through the power of natural language. However, navigating these models to generate unique concepts, alter their appearance, or reimagine them in unfamiliar roles presents an intricate challenge. For instance, how can we exploit language-guided models to transpose an anime character into a different art style, or envision a beloved character in a radically different setting or role? This paper unveils a novel approach named DreamAnime, designed to provide this level of creative freedom. Using a minimal set of 2-3 images of a user-specified concept such as an anime character …

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One-For-All: Towards Universal Domain Translation With A Single Stylegan, Yong Du, Jiahui Zhan, Xinzhe Li, Junyu Dong, Sheng Chen, Ming-Hsuan Yang, Shengfeng He Apr 2025

One-For-All: Towards Universal Domain Translation With A Single Stylegan, Yong Du, Jiahui Zhan, Xinzhe Li, Junyu Dong, Sheng Chen, Ming-Hsuan Yang, Shengfeng He

Research Collection School Of Computing and Information Systems

In this paper, we propose a novel translation model, UniTranslator, for transforming representations between visually distinct domains under conditions of limited training data and significant visual differences. The main idea behind our approach is leveraging the domain-neutral capabilities of CLIP as a bridging mechanism, while utilizing a separate module to extract abstract, domain-agnostic semantics from the embeddings of both the source and target realms. Fusing these abstract semantics with target-specific semantics results in a transformed embedding within the CLIP space. To bridge the gap between the disparate worlds of CLIP and StyleGAN, we introduce a new non-linear mapper, the CLIP2P …

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Visualization Of Paleocurrents On A Web Application Using Gplates, Anjan Sapkota Dec 2024

Visualization Of Paleocurrents On A Web Application Using Gplates, Anjan Sapkota

MS in Computer Science Theses

Paleocurrents are flow directions derived from features of sedimentary rocks that reveal the direction of the current of wind or water that deposited the sediment. In 2015, Brand et al. created a global database of paleocurrents, which contains over 1,000,000 measurements worldwide: North America, South America, Australia, Great Britain, parts of Western Europe, China, Africa are fairly well represented; Antarctica, Eastern Europe, and Asia are modestly represented and Russia is poorly represented. The contribution of this thesis is a web application that uses the GPlates’ Application Programming Interface (API) to visualize global paleocurrents through time in an interactive way based …

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Visualizing Routes With Ai-Discovered Street-View Patterns, Tsung Heng Wu, Md Amiruzzaman, Ye Zhao, Deepshikha Bhati, Jing Yang Apr 2024

Visualizing Routes With Ai-Discovered Street-View Patterns, Tsung Heng Wu, Md Amiruzzaman, Ye Zhao, Deepshikha Bhati, Jing Yang

Computer Science Faculty Publications

Street-level visual appearances play an important role in studying social systems, such as understanding the built environment, driving routes, and associated social and economic factors. It has not been integrated into a typical geographical visualization interface (e.g., map services) for planning driving routes. In this article, we study this new visualization task with several new contributions. First, we experiment with a set of AI techniques and propose a solution of using semantic latent vectors for quantifying visual appearance features. Second, we calculate image similarities among a large set of street-view images and then discover spatial imagery patterns. Third, we integrate …

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Human-Centered Machine Learning With Interpretable Visual Knowledge Discovery, Lincoln Huber Jan 2024

Human-Centered Machine Learning With Interpretable Visual Knowledge Discovery, Lincoln Huber

All Master's Theses

This research advances interpretable machine learning (ML) by introducing hyperblocks (HBs) as a structured, rule-based approach for creating transparent and accurate models using meaningful numeric attributes directly interpretable to end users. Key techniques, including Parallel Hyperblock Creation, Interactive Hyperblock Creation, Level n Hyperblock Creation, and k-Nearest Neighbor Hyperblock, provide a framework that ensures domain experts can meaningfully engage with the model’s decision-making process through lossless visualizations using General Line Coordinates (GLC). Case studies with the Wisconsin Breast Cancer and MNIST datasets demonstrated HBs' effectiveness in handling high-risk and complex classification tasks, offering interpretable accuracy that traditional models struggle to achieve. …

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Edge Distraction-Aware Salient Object Detection, Sucheng Ren, Wenxi Liu, Jianbo Jiao, Guoqiang Han, Shengfeng He Sep 2023

Edge Distraction-Aware Salient Object Detection, Sucheng Ren, Wenxi Liu, Jianbo Jiao, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

Integrating low-level edge features has been proven to be effective in preserving clear boundaries of salient objects. However, the locality of edge features makes it difficult to capture globally salient edges, leading to distraction in the final predictions. To address this problem, we propose to produce distraction-free edge features by incorporating cross-scale holistic interdependencies between high-level features. In particular, we first formulate our edge features extraction process as a boundary-filling problem. In this way, we enforce edge features to focus on closed boundaries instead of those disconnected background edges. Second, we propose to explore cross-scale holistic contextual connections between every …

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Ifundit: Visual Profiling Of Fund Investment Styles, Rong Zhang, Bon Kyung Ku, Yong Wang, Xuanwu Yue, Siyuan Liu, Ke Li, Huamin Qu Jun 2023

Ifundit: Visual Profiling Of Fund Investment Styles, Rong Zhang, Bon Kyung Ku, Yong Wang, Xuanwu Yue, Siyuan Liu, Ke Li, Huamin Qu

Research Collection School Of Computing and Information Systems

Mutual funds are becoming increasingly popular with the emergence of Internet finance. Clear profiling of a fund's investment style is crucial for fund managers to evaluate their investment strategies, and for investors to understand their investment. However, it is challenging to profile a fund's investment style as it requires a comprehensive analysis of complex multi-dimensional temporal data. In addition, different fund managers and investors have different focuses when analysing a fund's investment style. To address the issue, we propose iFUNDit, an interactive visual analytic system for fund investment style analysis. The system decomposes a fund's critical features into performance attributes …

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Gnnlens: A Visual Analytics Approach For Prediction Error Diagnosis Of Graph Neural Networks., Zhihua Jin, Yong Wang, Qianwen Wang, Yao Ming, Tengfei Ma, Huamin Qu Jun 2023

Gnnlens: A Visual Analytics Approach For Prediction Error Diagnosis Of Graph Neural Networks., Zhihua Jin, Yong Wang, Qianwen Wang, Yao Ming, Tengfei Ma, Huamin Qu

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) aim to extend deep learning techniques to graph data and have achieved significant progress in graph analysis tasks (e.g., node classification) in recent years. However, similar to other deep neural networks like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), GNNs behave like a black box with their details hidden from model developers and users. It is therefore difficult to diagnose possible errors of GNNs. Despite many visual analytics studies being done on CNNs and RNNs, little research has addressed the challenges for GNNs. This paper fills the research gap with an interactive visual analysis …

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Investigating Guardian Awareness Techniques To Promote Safety In Virtual Reality, Sixuan Wu, Jiannan Li, Maurício Sousa, Tovi Grossman Mar 2023

Investigating Guardian Awareness Techniques To Promote Safety In Virtual Reality, Sixuan Wu, Jiannan Li, Maurício Sousa, Tovi Grossman

Research Collection School Of Computing and Information Systems

Virtual Reality (VR) can completely immerse users in a virtual world and provide little awareness of bystanders in the surrounding physical environment. Current technologies use predefined guardian area visualizations to set safety boundaries for VR interactions. However, bystanders cannot perceive these boundaries and may collide with VR users if they accidentally enter guardian areas. In this paper, we investigate four awareness techniques on mobile phones and smartwatches to help bystanders avoid invading guardian areas. These techniques include augmented reality boundary overlays and visual, auditory, and haptic alerts indicating bystanders' distance from guardians. Our findings suggest that the proposed techniques effectively …

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Codebase Relationship Visualizer: Visualizing Relationships Between Source Code Files, Jesse Hines Jan 2023

Codebase Relationship Visualizer: Visualizing Relationships Between Source Code Files, Jesse Hines

MS in Computer Science Project Reports

Understanding relationships between files and their directory structure is a fundamental part of the software development process. However, it can be hard to grasp these relationships without a convenient way to visualize how files are connected and how they fit into the directory structure of the codebase. In this paper we describe CodeBase Relationship Visualizer (CBRV), a Visual Studio Code extension that interactively visualizes the relationships between files. CBRV displays the relationships between files as arrows superimposed over a diagram of the codebase's directory structure. CBRV comes bundled with visualizations of the stack trace path, a dependency graph for Python …

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Visualization Teaching Tool For Computational Geometry Algorithms, Seth Spire Jan 2023

Visualization Teaching Tool For Computational Geometry Algorithms, Seth Spire

Honors Projects

Computational geometry is a branch of computer science dedicated to the study and development of algorithms that solve geometric problems. These algorithms are often complex, so this project involves the development of a teaching tool for various computational geometry algorithms. A Node app was developed which allows a user to create their own inputs for an algorithm and watch a visualization of how an algorithm solves one of the various problems. There is highlighted pseudocode matching the steps of the visualization along with more in-depth writeups of the inner workings of the algorithm. 4 algorithms have been implemented in the …

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Cross-Modal Food Retrieval: Learning A Joint Embedding Of Food Images And Recipes With Semantic Consistency And Attention Mechanism, Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi Jan 2022

Cross-Modal Food Retrieval: Learning A Joint Embedding Of Food Images And Recipes With Semantic Consistency And Attention Mechanism, Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Food retrieval is an important task to perform analysis of food-related information, where we are interested in retrieving relevant information about the queried food item such as ingredients, cooking instructions, etc. In this paper, we investigate cross-modal retrieval between food images and cooking recipes. The goal is to learn an embedding of images and recipes in a common feature space, such that the corresponding image-recipe embeddings lie close to one another. Two major challenges in addressing this problem are 1) large intra-variance and small inter-variance across cross-modal food data; and 2) difficulties in obtaining discriminative recipe representations. To address these …

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Cross-Modal Food Retrieval: Learning A Joint Embedding Of Food Images And Recipes With Semantic Consistency And Attention Mechanism;, Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Achananuparp Palakorn, Ee Peng Lim, Steven Hoi May 2021

Cross-Modal Food Retrieval: Learning A Joint Embedding Of Food Images And Recipes With Semantic Consistency And Attention Mechanism;, Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Achananuparp Palakorn, Ee Peng Lim, Steven Hoi

Research Collection School Of Computing and Information Systems

Food retrieval is an important task to perform analysis of food-related information, where we are interested in retrieving relevant information about the queried food item such as ingredients, cooking instructions, etc. In this paper, we investigate cross-modal retrieval between food images and cooking recipes. The goal is to learn an embedding of images and recipes in a common feature space, such that the corresponding image-recipe embeddings lie close to one another. Two major challenges in addressing this problem are 1) large intra-variance and small inter-variance across cross-modal food data; and 2) difficulties in obtaining discriminative recipe representations. To address these …

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Evaluating Grasping Visualizations And Control Modes In A Vr Game, Alex Adkins, Lorraine Lin, Aline Normoyle, Ryan Canales, Yuting Ye, Sophie Jörg Jan 2021

Evaluating Grasping Visualizations And Control Modes In A Vr Game, Alex Adkins, Lorraine Lin, Aline Normoyle, Ryan Canales, Yuting Ye, Sophie Jörg

Computer Science Faculty Research and Scholarship

A primary goal of the Virtual Reality(VR) community is to build fully immersive and presence-inducing environments with seamless and natural interactions. To reach this goal, researchers are investigating how to best directly use our hands to interact with a virtual environment using hand tracking. Most studies in this field require participants to perform repetitive tasks. In this article, we investigate if results of such studies translate into a real application and game-like experience. We designed a virtual escape room in which participants interact with various objects to gather clues and complete puzzles. In a between-subjects study, we examine the effects …

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Soda: An Open-Source Library For Visualizing Biological Sequence Annotation, Jack W. Roddy, Travis J. Wheeler Jan 2021

Soda: An Open-Source Library For Visualizing Biological Sequence Annotation, Jack W. Roddy, Travis J. Wheeler

Graduate Student Theses, Dissertations, & Professional Papers

Genome annotation is the process of identifying and labeling known genetic sequences or features within a genome. Across the various subfields within modern molecular biology, there is a common need for the visualization of such annotations. Genomic data is often visualized on web browser platforms, providing users with easy access to visualization tools without the need for installing any software or, in many cases, underlying datasets. While there exists a broad range of web-based visualization tools, there is, to my knowledge, no lightweight, modern library tailored towards the visualization of genomic data. Instead, developers charged with the task of producing …

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A Study Of Multi-Task And Region-Wise Deep Learning For Food Ingredient Recognition, Jingjing Chen, Bin Zhu, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang Dec 2020

A Study Of Multi-Task And Region-Wise Deep Learning For Food Ingredient Recognition, Jingjing Chen, Bin Zhu, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Food recognition has captured numerous research attention for its importance for health-related applications. The existing approaches mostly focus on the categorization of food according to dish names, while ignoring the underlying ingredient composition. In reality, two dishes with the same name do not necessarily share the exact list of ingredients. Therefore, the dishes under the same food category are not mandatorily equal in nutrition content. Nevertheless, due to limited datasets available with ingredient labels, the problem of ingredient recognition is often overlooked. Furthermore, as the number of ingredients is expected to be much less than the number of food categories, …

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Visualocv: Refined Dataflow Programming Interface For Opencv, John Boggess Aug 2020

Visualocv: Refined Dataflow Programming Interface For Opencv, John Boggess

MS in Computer Science Project Reports

OpenCV is a popular tool for developing computer vision algorithms; however, prototyping OpenCV-based algorithms is a time consuming and iterative process. VisualOCV is an open source tool to help users better understand and create computer vision algorithms. A user can see how data is processed at each step in their algorithm, and the results of any changes to the algorithm will be displayed to the user immediately. This can allow the user to easily experiment with various computer vision methods and their parameters. EyeCalc 1.0 uses the Microsoft Foundation Class Library, an old GUI framework by Microsoft, and contains various …

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The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Adam Kern Apr 2020

The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Adam Kern

McKelvey School of Engineering Graduate Student Theses & Dissertations

The main purpose of information visualization is to act as a window between a user and data. Historically, this has been accomplished via a single-agent framework: the only decisionmaker in the relationship between visualization system and analyst is the analyst herself. Yet this framework arose not from first principles, but from necessity: prior to this decade, computers were limited in their decision-making capabilities, especially in the face of large, complex datasets and visualization systems. This thesis aims to present the design and evaluation of a mixed-initiative system that aids the user in handling large, complex datasets and dense visualization systems. …

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Neighbourhood Structure Preserving Cross-Modal Embedding For Video Hyperlinking, Yanbin Hao, Chong-Wah Ngo, Benoit Huet Jan 2020

Neighbourhood Structure Preserving Cross-Modal Embedding For Video Hyperlinking, Yanbin Hao, Chong-Wah Ngo, Benoit Huet

Research Collection School Of Computing and Information Systems

Video hyperlinking is a task aiming to enhance the accessibility of large archives, by establishing links between fragments of videos. The links model the aboutness between fragments for efficient traversal of video content. This paper addresses the problem of link construction from the perspective of cross-modal embedding. To this end, a generalized multi-modal auto-encoder is proposed.& x00A0;The encoder learns two embeddings from visual and speech modalities, respectively, whereas each of the embeddings performs self-modal and cross-modal translation of modalities. Furthermore, to preserve the neighbourhood structure of fragments, which is important for video hyperlinking, the auto-encoder is devised to model data …

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Nonuniform Timeslicing Of Dynamic Graphs Based On Visual Complexity, Yong Wang, Daniel Archambault, Hammad Haleem, Torsten Moeller, Yanhong Wu, Huamin Qu Oct 2019

Nonuniform Timeslicing Of Dynamic Graphs Based On Visual Complexity, Yong Wang, Daniel Archambault, Hammad Haleem, Torsten Moeller, Yanhong Wu, Huamin Qu

Research Collection School Of Computing and Information Systems

Uniform timeslicing of dynamic graphs has been used due to its convenience and uniformity across the time dimension. However, uniform timeslicing does not take the data set into account, which can generate cluttered timeslices with edge bursts and empty timeslices with few interactions. The graph mining filed has explored nonuniform timeslicing methods specifically designed to preserve graph features for mining tasks. In this paper, we propose a nonuni-form timeslicing approach for dynamic graph visualization. Our goal is to create timeslices of equal visual complexity. To this end, we adapt histogram equalization to create timeslices with a similar number of events, …

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U.S. Census Explorer: A Gui And Visualization Tool For The U.S. Census Data Api, Timothy Snyder Jan 2019

U.S. Census Explorer: A Gui And Visualization Tool For The U.S. Census Data Api, Timothy Snyder

Williams Honors College, Honors Research Projects

U.S. Census Explorer is a software application that is designed to provide tools for intuitive exploration and analysis of United States census data for non-technical users. The application serves as an interface into the U.S. Census Bureau’s data API that enables a complete workflow from data acquisition to data visualization without the need for technical intervention from the user. The suite of tools provided include a graphical user interface for dynamically querying U.S. census data, geographic visualizations, and the ability to download your work to common spreadsheet and image formats for inclusion in external works.

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Big Data Visualization Platform For Mixed Reality, Aliakbar Panahi Jan 2017

Big Data Visualization Platform For Mixed Reality, Aliakbar Panahi

Theses and Dissertations

The visualization of data helps to provide faster and deeper insight into the data. In this work, a system for visualizing and analyzing big data in an interactive mixed reality environment is proposed. Such a system can be used for representing different types of data such as temporal, geospatial, network graph, and high dimensional. Also, an implementation of this system for four different data types are created. The data types include network data, volumetric data, high dimensional, and spectral data for different mixed reality devices such as Microsoft HoloLens, Oculus Rift, Samsung Gear VR, and Android ARCore were created. It …

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Hindsight: Encouraging Exploration Through Direct Encoding Of Personal Interaction History, Mi Feng, Cheng Deng, Evan M. Peck, Lane Harrison Jan 2017

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 …

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Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang Jun 2016

Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang

Research Collection School Of Computing and Information Systems

Top-down saliency detection is a knowledge-driven search task. While some previous methods aim to learn this "knowledge" from category-specific data, others transfer existing annotations in a large dataset through appearance matching. In contrast, we propose in this paper a locateby-exemplar strategy. This approach is challenging, as we only use a few exemplars (up to 4) and the appearances among the query object and the exemplars can be very different. To address it, we design a two-stage deep model to learn the intra-class association between the exemplars and query objects. The first stage is for learning object-to-object association, and the second …

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Ambiguityvis: Visualization Of Ambiguity In Graph Layouts, Yong Wang, Qiaomu Shen, Zhiguang Zhou, Min Zhu, Sixiao Yang, Qu Huamin Jan 2016

Ambiguityvis: Visualization Of Ambiguity In Graph Layouts, Yong Wang, Qiaomu Shen, Zhiguang Zhou, Min Zhu, Sixiao Yang, Qu Huamin

Research Collection School Of Computing and Information Systems

Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graph layout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteria simultaneously, producing drawings with visual ambiguities that can impede the understanding of network structure. To bring attention to these potentially problematic areas present in the drawing. this paper presents a technique that highlights common types of visual ambiguities: ambiguous spatial relationships between nodes and edges, visual overlap between community structures, and ambiguity in edge bundling and metanodes. Metrics, including newly proposed metrics for abnormal edge …

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Interpretation At The Controller's Edge: The Role Of Graphical User Interfaces In Virtual Archaeology, Tyler Duane Johnson May 2015

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 …

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Visual Analytics For Large Communication Trace Data, Jieting Wu Apr 2015

Visual Analytics For Large Communication Trace Data, Jieting Wu

School of Computing: Dissertations, Theses, and Student Research

Executions of modern parallel programs often yield complex communications among compute nodes of large-scale clusters of workstations or supercomputers. Analyzing communication patterns is becoming increasingly critical to performance optimiza- tion. As the scale and complexity of parallel applications drastically increases, visu- alization has become a feasible means to conduct analysis of massive communication patterns. However, most visualization tools fall short in showing comprehensive dy- namic communication graph and addressing the scalability issue. Our solution for analyzing dynamic communication patterns is based on an analytics framework cou- pled with a new visualization technique, named CommGram [29], that provides a flexible solution …

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Physio@Home: Exploring Visual Guidance And Feedback Techniques For Physiotherapy Exercises, Richard Tang, Xing-Dong Yang, Scott Bateman, Joaquim Jorge, Anthony Tang Apr 2015

Physio@Home: Exploring Visual Guidance And Feedback Techniques For Physiotherapy Exercises, Richard Tang, Xing-Dong Yang, Scott Bateman, Joaquim Jorge, Anthony Tang

Research Collection School Of Computing and Information Systems

Physiotherapy patients exercising at home alone are at risk of re-injury since they do not have corrective guidance from a therapist. To explore solutions to this problem, we designed Physio@Home, a prototype that guides people through pre-recorded physiotherapy exercises using realtime visual guides and multi-camera views. Our design addresses several aspects of corrective guidance, including: plane and range of movement, joint positions and angles, and extent of movement. We evaluated our design, comparing how closely people could follow exercise movements under various feedback conditions. Participants were most accurate when using our visual guide and multi-views. We provide suggestions for exercise …

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Digital Forensics Tool Interface Visualization, Roberto A. Altiero Jan 2015

Digital Forensics Tool Interface Visualization, Roberto A. Altiero

CCAC Theses and Dissertations

Recent trends show digital devices utilized with increasing frequency in most crimes committed. Investigating crime involving these devices is labor-intensive for the practitioner applying digital forensics tools that present possible evidence with results displayed in tabular lists for manual review. This research investigates how enhanced digital forensics tool interface visualization techniques can be shown to improve the investigator's cognitive capacities to discover criminal evidence more efficiently. This paper presents visualization graphs and contrasts their properties with the outputs of The Sleuth Kit (TSK) digital forensic program. Exhibited is the textual-based interface proving the effectiveness of enhanced data presentation. Further demonstrated …

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