Matching Items (15)

Creative Project: Dale and Edna

Description

Dale and Edna is a hybrid animated film and videogame experienced in virtual reality with dual storylines that increases in potential meanings through player interaction. Developed and played within Unreal

Dale and Edna is a hybrid animated film and videogame experienced in virtual reality with dual storylines that increases in potential meanings through player interaction. Developed and played within Unreal Engine 4 using the HTC Vive, Oculus, or PlayStation VR, Dale and Edna allows for players to passively enjoy the film element of the project or partake in the active videogame portion. Exploration of the virtual story world yields more information about that world, which may or may not alter the audience’s perception of the world. The film portion of the project is a static narrative with a plot that cannot be altered by players within the virtual world. In the static plot, the characters Dale and Edna discover and subsequently combat an alien invasion that appears to have the objective of demolishing Dale’s prize pumpkin. However, the aliens in the film plot are merely projections created by AR headsets that are reflecting Jimmy’s gameplay on his tablet. The audience is thus invited to question their perception of reality through combined use of VR and AR. The game element is a dynamic narrative scaffold that does not unfold as a traditional narrative might. Instead, what a player observes and interacts with within the sandbox level will determine the meaning those players come away from this project with. Both elements of the project feature modular code construction so developers can return to both the film and game portions of the project and make additions. This paper will analyze the chronological development of the project along with the guiding philosophy that was revealed in the result.
Keywords: virtual reality, film, videogame, sandbox

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Agent

Created

Date Created
  • 2019-05

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ECOAcoustic: A VR Experience

Description

Acoustic Ecology is an undervalued field of study of the relationship between the environment and sound. This project aims to educate people on this topic and show people the importance

Acoustic Ecology is an undervalued field of study of the relationship between the environment and sound. This project aims to educate people on this topic and show people the importance by immersing them in virtual reality scenes. The scenes were created using VR180 content as well as 360° spatial audio.

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Agent

Created

Date Created
  • 2019-05

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Battleship: A Case Study of the Augmented Reality User Experience

Description

Emerging technologies, such as augmented reality (AR), are growing in popularity and accessibility at a fast pace. Developers are building more and more games and applications with this technology but

Emerging technologies, such as augmented reality (AR), are growing in popularity and accessibility at a fast pace. Developers are building more and more games and applications with this technology but few have stopped to think about what the best practices are for creating a good user experience (UX). Currently, there are no universally accepted human-computer interaction guidelines for augmented reality because it is still relatively new. This paper examines three features - virtual content scale, indirect selection, and virtual buttons - in an attempt to discover their impact on the user experience in augmented reality. A Battleship game was developed using the Unity game engine with Vuforia, an augmented reality platform, and built as an iOS application to test these features. The hypothesis was that both virtual content scale and indirect selection would result in a more enjoyable and engaging user experience whereas the virtual button would be too confusing for users to fully appreciate the feature. Usability testing was conducted to gauge participants' responses to these features. After playing a base version of the game with no additional features and then a second version with one of the three features, participants rated their experiences and provided feedback in a four-part survey. It was observed during testing that people did not inherently move their devices around the augmented space and needed guidance to navigate the game. Most users were fascinated with the visuals of the game and two of the tested features. It was found that movement around the augmented space and feedback from the virtual content were critical aspects in creating a good user experience in augmented reality.

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Created

Date Created
  • 2018-05

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leARn: Supplementing Proven Teaching Techniques with AR Tools

Description

Augmented Reality (AR) is a tool increasingly available to young learners and educators. This paper documents and analyzes the creation of an AR app used as a tool to teach

Augmented Reality (AR) is a tool increasingly available to young learners and educators. This paper documents and analyzes the creation of an AR app used as a tool to teach fractions to young learners and enhance their engagement in the classroom. As an emerging technology reaching diffusion into the general populace, AR presents a unique opportunity to engage users in the digital and real world. Additionally, AR can be enabled on most modern phones and tablets; therefore, it is extremely accessible and has a low barrier to entry. To integrate AR into the classroom in an affordable way, I created leARn, an AR application intended to help young learners understand fractions. leARn is an application intended to be used alongside traditional teaching methods, in order to enhance the engagement of students in the classroom. Throughout the development of the product, I not only considered usability and design, but also the effectiveness of the app in the classroom. Moreover, due to collaboration with Arizona State University Research Enterprises, I tested the application in a classroom with sixth, seventh and eighth grade students. This paper presents the findings from that testing period and analysis of the educational effectiveness of the concept based on data received from students.

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Created

Date Created
  • 2019-05

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Exploring the Influence of Visualized Data: Inclusion and Collaboration Between University Members

Description

Visualizations are an integral component for communicating and evaluating modern networks. As data becomes more complex, info-graphics require a balance between visual noise and effective storytelling that is often restricted

Visualizations are an integral component for communicating and evaluating modern networks. As data becomes more complex, info-graphics require a balance between visual noise and effective storytelling that is often restricted by layouts unsuitable for scalability. The challenge then rests upon researchers to effectively structure their information in a way that allows for flexible, transparent illustration. We propose network graphing as an operative alternative for demonstrating community behavior over traditional charts which are unable to look past numeric data. In this paper, we explore methods for manipulating, processing, cleaning, and aggregating data in Python; a programming language tailored for handling structured data, which can then be formatted for analysis and modeling of social network tendencies in Gephi. We implement this data by applying an algorithm known as the Fruchterman-Reingold force-directed layout to datasets of Arizona State University’s research and collaboration network. The result is a visualization that analyzes the university’s infrastructure by providing insight about community behaviors between colleges. Furthermore, we highlight how the flexibility of this visualization provides a foundation for specific use cases by demonstrating centrality measures to find important liaisons that connect distant communities.

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Date Created
  • 2020-05

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Investigating Methods of Achieving Photorealistic Materials for Augmented Reality Applications on Mobile Devices

Description

As the prevalence of augmented reality (AR) technology continues to increase, so too have methods for improving the appearance and behavior of computer-generated objects. This is especially significant as

As the prevalence of augmented reality (AR) technology continues to increase, so too have methods for improving the appearance and behavior of computer-generated objects. This is especially significant as AR applications now expand to territories outside of the entertainment sphere and can be utilized for numerous purposes encompassing but not limited to education, specialized occupational training, retail & online shopping, design, marketing, and manufacturing. Due to the nature of AR technology, where computer-generated objects are being placed into a real-world environment, a decision has to be made regarding the visual connection between the tangible and the intangible. Should the objects blend seamlessly into their environment or purposefully stand out? It is not purely a stylistic choice. A developer must consider how their application will be used — in many instances an optimal user experience is facilitated by mimicking the real world as closely as possible; even simpler applications, such as those built primarily for mobile devices, can benefit from realistic AR. The struggle here lies in creating an immersive user experience that is not reliant on computationally-expensive graphics or heavy-duty models. The research contained in this thesis provides several ways for achieving photorealistic rendering in AR applications using a range of techniques, all of which are supported on mobile devices. These methods can be employed within the Unity Game Engine and incorporate shaders, render pipelines, node-based editors, post-processing, and light estimation.

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Created

Date Created
  • 2020-05

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Thermal noise analysis of near-sensor image processing

Description

Commonly, image processing is handled on a CPU that is connected to the image sensor by a wire. In these far-sensor processing architectures, there is energy loss associated with sending

Commonly, image processing is handled on a CPU that is connected to the image sensor by a wire. In these far-sensor processing architectures, there is energy loss associated with sending data across an interconnect from the sensor to the CPU. In an effort to increase energy efficiency, near-sensor processing architectures have been developed, in which the sensor and processor are stacked directly on top of each other. This reduces energy loss associated with sending data off-sensor. However, processing near the image sensor causes the sensor to heat up. Reports of thermal noise in near-sensor processing architectures motivated us to study how temperature affects image quality on a commercial image sensor and how thermal noise affects computer vision task accuracy. We analyzed image noise across nine different temperatures and three sensor configurations to determine how image noise responds to an increase in temperature. Ultimately, our team used this information, along with transient analysis of a stacked image sensor’s thermal behavior, to advise thermal management strategies that leverage the benefits of near-sensor processing and prevent accuracy loss at problematic temperatures.

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Date Created
  • 2020-12

Characterization of Energy and Performance Bottlenecks in an Omni-directional Camera System

Description

Generating real-world content for VR is challenging in terms of capturing and processing at high resolution and high frame-rates. The content needs to represent a truly immersive experience, where the

Generating real-world content for VR is challenging in terms of capturing and processing at high resolution and high frame-rates. The content needs to represent a truly immersive experience, where the user can look around in 360-degree view and perceive the depth of the scene. The existing solutions only capture and offload the compute load to the server. But offloading large amounts of raw camera feeds takes longer latencies and poses difficulties for real-time applications. By capturing and computing on the edge, we can closely integrate the systems and optimize for low latency. However, moving the traditional stitching algorithms to battery constrained device needs at least three orders of magnitude reduction in power. We believe that close integration of capture and compute stages will lead to reduced overall system power.

We approach the problem by building a hardware prototype and characterize the end-to-end system bottlenecks of power and performance. The prototype has 6 IMX274 cameras and uses Nvidia Jetson TX2 development board for capture and computation. We found that capturing is bottlenecked by sensor power and data-rates across interfaces, whereas compute is limited by the total number of computations per frame. Our characterization shows that redundant capture and redundant computations lead to high power, huge memory footprint, and high latency. The existing systems lack hardware-software co-design aspects, leading to excessive data transfers across the interfaces and expensive computations within the individual subsystems. Finally, we propose mechanisms to optimize the system for low power and low latency. We emphasize the importance of co-design of different subsystems to reduce and reuse the data. For example, reusing the motion vectors of the ISP stage reduces the memory footprint of the stereo correspondence stage. Our estimates show that pipelining and parallelization on custom FPGA can achieve real time stitching.

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Created

Date Created
  • 2018

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Generating Light Estimation for Mixed-reality Devices through Collaborative Visual Sensing

Description

Mixed reality mobile platforms co-locate virtual objects with physical spaces, creating immersive user experiences. To create visual harmony between virtual and physical spaces, the virtual scene must be accurately illuminated

Mixed reality mobile platforms co-locate virtual objects with physical spaces, creating immersive user experiences. To create visual harmony between virtual and physical spaces, the virtual scene must be accurately illuminated with realistic physical lighting. To this end, a system was designed that Generates Light Estimation Across Mixed-reality (GLEAM) devices to continually sense realistic lighting of a physical scene in all directions. GLEAM optionally operate across multiple mobile mixed-reality devices to leverage collaborative multi-viewpoint sensing for improved estimation. The system implements policies that prioritize resolution, coverage, or update interval of the illumination estimation depending on the situational needs of the virtual scene and physical environment.

To evaluate the runtime performance and perceptual efficacy of the system, GLEAM was implemented on the Unity 3D Game Engine. The implementation was deployed on Android and iOS devices. On these implementations, GLEAM can prioritize dynamic estimation with update intervals as low as 15 ms or prioritize high spatial quality with update intervals of 200 ms. User studies across 99 participants and 26 scene comparisons reported a preference towards GLEAM over other lighting techniques in 66.67% of the presented augmented scenes and indifference in 12.57% of the scenes. A controlled lighting user study on 18 participants revealed a general preference for policies that strike a balance between resolution and update rate.

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Created

Date Created
  • 2018

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Computer Vision from Spatial-Multiplexing Cameras at Low Measurement Rates

Description

In UAVs and parking lots, it is typical to first collect an enormous number of pixels using conventional imagers. This is followed by employment of expensive methods to compress by

In UAVs and parking lots, it is typical to first collect an enormous number of pixels using conventional imagers. This is followed by employment of expensive methods to compress by throwing away redundant data. Subsequently, the compressed data is transmitted to a ground station. The past decade has seen the emergence of novel imagers called spatial-multiplexing cameras, which offer compression at the sensing level itself by providing an arbitrary linear measurements of the scene instead of pixel-based sampling. In this dissertation, I discuss various approaches for effective information extraction from spatial-multiplexing measurements and present the trade-offs between reliability of the performance and computational/storage load of the system. In the first part, I present a reconstruction-free approach to high-level inference in computer vision, wherein I consider the specific case of activity analysis, and show that using correlation filters, one can perform effective action recognition and localization directly from a class of spatial-multiplexing cameras, called compressive cameras, even at very low measurement rates of 1\%. In the second part, I outline a deep learning based non-iterative and real-time algorithm to reconstruct images from compressively sensed (CS) measurements, which can outperform the traditional iterative CS reconstruction algorithms in terms of reconstruction quality and time complexity, especially at low measurement rates. To overcome the limitations of compressive cameras, which are operated with random measurements and not particularly tuned to any task, in the third part of the dissertation, I propose a method to design spatial-multiplexing measurements, which are tuned to facilitate the easy extraction of features that are useful in computer vision tasks like object tracking. The work presented in the dissertation provides sufficient evidence to high-level inference in computer vision at extremely low measurement rates, and hence allows us to think about the possibility of revamping the current day computer systems.

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Created

Date Created
  • 2017