ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at firstname.lastname@example.org.
- 3 English
- 3 Public
- Computer engineering
- 2 Electrical engineering
- 1 360 camera systems
- 1 Computer Vision
- 1 Computer science
- 1 Embedded Systems
- 1 Image Signal Processing
- 1 Mobile Systems
- 1 Omnidirectional Camera
- 1 advanced driver assistance systems
- 1 deep neural networks
- 1 generative adversarial networks
- 1 inverse perspective mapping
- 1 object detection
- 1 obstacle detection
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 …
- Gunnam, Sridhar, LiKamWa, Robert, Turaga, Pavan, et al.
- Created Date
Object detection is an interesting computer vision area that is concerned with the detection of object instances belonging to specific classes of interest as well as the localization of these instances in images and/or videos. Object detection serves as a vital module in many computer vision based applications. This work focuses on the development of object detection methods that exhibit increased robustness to varying illuminations and image quality. In this work, two methods for robust object detection are presented. In the context of varying illumination, this work focuses on robust generic obstacle detection and collision warning in Advanced Driver Assistance …
- PRAKASH, CHARAN DUDDA, Karam, Lina, Abousleman, Glen, et al.
- Created Date
This thesis addresses the problem of recommending a viewpoint for aesthetic photography. Viewpoint recommendation is suggesting the best camera pose to capture a visually pleasing photograph of the subject of interest by using any end-user device such as drone, mobile robot or smartphone. Solving this problem enables to capture visually pleasing photographs autonomously in areal photography, wildlife photography, landscape photography or in personal photography. The viewpoint recommendation problem can be divided into two stages: (a) generating a set of dense novel views based on the basis views captured about the subject. The dense novel views are useful to better understand …
- Katukuri, Sathish Kumar, LiKamWa, Robert, Turaga, Pavan, et al.
- Created Date