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Full-Text Articles in Physical Sciences and Mathematics
Towards Color-Based Two-Hand 3d Global Pose Estimation, Fanqing Lin
Towards Color-Based Two-Hand 3d Global Pose Estimation, Fanqing Lin
Theses and Dissertations
Pose estimation and tracking is essential for applications involving human controls. Specifically, as the primary operating tool for human activities, hand pose estimation plays a significant role in applications such as hand tracking, gesture recognition, human-computer interaction and VR/AR. As the field develops, there has been a trend to utilize deep learning to estimate the 2D/3D hand poses using color-based information without depth data. Within the depth-based as well as color-based approaches, the research community has primarily focused on single-hand scenarios in a localized/normalized coordinate system. Due to the fact that both hands are utilized in most applications, we propose …
Deep Parameter Selection For Classic Computer Vision Applications, Michael Whitney
Deep Parameter Selection For Classic Computer Vision Applications, Michael Whitney
Theses and Dissertations
A trend in computer vision today is to retire older, so-called "classic'' methods in favor of ones based on deep neural networks. This has led to tremendous improvements in many areas, but for some problems deep neural solutions may not yet exist or be of practical application. For this and other reasons, classic methods are still widely used in a variety of applications. This paper explores the possibility of using deep neural networks to improve these older methods instead of replace them. In particular, it addresses the issue of parameter selection in these algorithms by using a neural network to …
The "What"-"Where" Network: A Tool For One-Shot Image Recognition And Localization, Daniel Hurlburt
The "What"-"Where" Network: A Tool For One-Shot Image Recognition And Localization, Daniel Hurlburt
Theses and Dissertations
One common shortcoming of modern computer vision is the inability of most models to generalize to new classes—one/few shot image recognition. We propose a new problem formulation for this task and present a network architecture and training methodology to solve this task. Further, we provide insights into how careful focus on how not just the data, but the way data presented to the model can have significant impact on performance. Using these method, we achieve high accuracy in few-shot image recognition tasks.
Facing The Hard Problems In Fgvc, Connor Stanley Anderson
Facing The Hard Problems In Fgvc, Connor Stanley Anderson
Theses and Dissertations
In fine-grained visual categorization (FGVC), there is a near-singular focus in pursuit of attaining state-of-the-art (SOTA) accuracy. This work carefully analyzes the performance of recent SOTA methods, quantitatively, but more importantly, qualitatively. We show that these models universally struggle with certain "hard" images, while also making complementary mistakes. We underscore the importance of such analysis, and demonstrate that combining complementary models can improve accuracy on the popular CUB-200 dataset by over 5%. In addition to detailed analysis and characterization of the errors made by these SOTA methods, we provide a clear set of recommended directions for future FGVC researchers.
Shadow Patching: Exemplar-Based Shadow Removal, Ryan Sears Hintze
Shadow Patching: Exemplar-Based Shadow Removal, Ryan Sears Hintze
Theses and Dissertations
Shadow removal is an important problem for both artists and algorithms. Previous methods handle some shadows well but, because they rely on the shadowed data, perform poorly in cases with severe degradation. Image-completion algorithms can completely replace severely degraded shadowed regions, and perform well with smaller-scale textures, but often fail to reproduce larger-scale macrostructure that may still be visible in the shadowed region. This paper provides a general framework that leverages degraded (e.g., shadowed) data to guide the image completion process by extending the objective function commonly used in current state-of-the-art image completion energy-minimization methods. This approach achieves realistic shadow …
Using Declassified Satellite Imagery To Quantify Geomorphic Change: A New Approach And Application To Himalayan Glaciers, Joshua Michael Maurer
Using Declassified Satellite Imagery To Quantify Geomorphic Change: A New Approach And Application To Himalayan Glaciers, Joshua Michael Maurer
Theses and Dissertations
Himalayan glaciers are key components of earth's cryosphere, acting as hydrological reservoirs vital to many human and natural systems. Most Himalayan glaciers are shrinking in response to changing climate, which will potentially impact water resources, natural hazards, sea level rise, and many other aspects. However, there is much uncertainty regarding the state of these glaciers, as direct field data are difficult to obtain. Accordingly, long-timespan remote sensing techniques are needed to measure changing glaciers, which have memory and often respond to climate on decadal timescales. This study uses declassified historical imagery from the Hexagon spy satellite database to fulfill this …
Face Tracking User Interfaces Using Vision-Based Consumer Devices, Norman Villaroman
Face Tracking User Interfaces Using Vision-Based Consumer Devices, Norman Villaroman
Theses and Dissertations
Some individuals have difficulty using standard hand-manipulated input devices such as a mouse and a keyboard effectively. For such users who at the same time have sufficient control over face and head movement, a robust perceptual or vision-based user interface that can track face movement can significantly help them. Using vision-based consumer devices makes such a user interface readily available and allows its use to be non-intrusive. Designing this type of user interface presents some significant challenges particularly with accuracy and usability. This research investigates such problems and proposes solutions to create a usable and robust face tracking user interface …
A See-Ability Metric To Improve Mini Unmanned Aerial Vehicle Operator Awareness Using Video Georegistered To Terrain Models, Cameron Howard Engh
A See-Ability Metric To Improve Mini Unmanned Aerial Vehicle Operator Awareness Using Video Georegistered To Terrain Models, Cameron Howard Engh
Theses and Dissertations
Search and rescue operations conducted in wilderness environments can be greatly aided by the use of video filmed from mini-UAVs. While lightweight, inexpensive and easily transportable, these small aircraft suffer from wind buffeting and may produce video that is difficult to search. To aid in the video search process, we have created a system to project video frames into a 3D representation of the search region. This projection allows us to tie each frame of video to a real-world location, enabling a myriad of novel views, mosaics and metrics that can be used to guide the search including a new …
Live Surface, Christopher J. Armstrong
Live Surface, Christopher J. Armstrong
Theses and Dissertations
Live Surface allows users to segment and render complex surfaces from 3D image volumes at interactive (sub-second) rates using a novel, Cascading Graph Cut (CGC). Live Surface consists of two phases. (1) Preprocessing for generation of a complete 3D watershed hierarchy followed by tracking of all catchment basin surfaces. (2) User interaction in which, with each mouse movement, the 3D object is selected and rendered in real time. Real-time segmentation is ccomplished by cascading through the 3D watershed hierarchy from the top, applying graph cut successively at each level only to catchment basins bordering the segmented surface from the previous …
Constraint-Based Interpolation, Daniel David Goggins
Constraint-Based Interpolation, Daniel David Goggins
Theses and Dissertations
Image reconstruction is the process of converting a sampled image into a continuous one prior to transformation and resampling. This reconstruction can be more accurate if two things are known: the process by which the sampled image was obtained and the general characteristics of the original image. We present a new reconstruction algorithm known as Constraint-Based Interpolation, which estimates the sampling functions found in cameras and analyzes properties of real world images in order to produce quality real-world image magnifications. To accomplish this, Constraint-Based Interpolation uses a sensor model that pushes the pixels in an interpolation to more closely match …