This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
Search
Skip to Search Results- 39Computer Vision
- 10Machine Learning
- 9Deep Learning
- 4Convolutional Neural Networks
- 4Robotics
- 33D Reconstruction
-
Fall 2023
Conventional control of an articulated manipulator such as robot arms involves the use of sensor measurements of joint values to calculate the position and orientation of the end-effector and to perform motion control. Conversely, in cases where direct sensing is not available, a vision-based...
-
Fall 2023
Unmanned aerial vehicles or UAVs have largely become and continue to be an inseparable part of modern warfare, security and surveillance systems, first aid response, aerial cinematography and many other sectors. Therefore, achieving full autonomy for UAVs and drones would ensure mass mobilization...
-
Fall 2024
Deep learning-based segmentation plays a crucial role in computer and robot vision. Traditional approaches have predominantly relied on RGB (i.e., color) imagery, given its widespread availability and usage. However, the innate issues with color imagery, such as cluttered backgrounds and poor...
-
Fall 2015
Determining the viewpoint (pose) of rigid objects in images is a classic vision problem with applications to robotic grasping, autonomous navigation, augmented reality, semantic SLAM and scene understanding in general. While most existing work is characterized by phrases such as "coarse pose...
-
Estimation of Ground Reaction Force Based on Computer Vision and Mobile Sensing for Floor Vibration Assessment
DownloadFall 2024
Floor vibrations caused by human activities, such as walking and running, should typically be addressed during the design phase. However, post-construction evaluations often fail to revisit these vibrations. This gap suggests a need for ongoing assessments to ensure that ...
-
Fall 2019
Object detection is an image processing technology to detection different classes of objects using computer vision, i.e. putting bounding boxes over objects from a camera video feed. A landmark detection method was the Viola-Jones Algorithm introduced in 2001. The object classifier in this...
-
Fall 2023
This thesis introduces a new approach for grounding concepts to vision using visual descriptions, which are text-based descriptions of visual attributes. We hypothesize that these descriptions can enhance the grounding of concepts to vision, thereby improving performance in vision-language tasks....
-
Spring 2024
Human pose estimation and shape modeling serve as critical elements in a wide range of computer vision applications. While most existing research employs RGB cameras for their accessibility and cost-effectiveness, emerging camera technologies and imaging modalities are relatively underexplored....
-
Image Registration with Homography: A Refresher with Differentiable Mutual Information, Ordinary Differential Equation and Complex Matrix Exponential
DownloadFall 2020
This work presents a novel method of tackling the task of image registration. Our algorithm uses a differentiable form of Mutual Information implemented via a neural network called MINE. An important property of neural networks is them being differentiable, which allows them to be used as a loss...
-
Fall 2022
Convolution Neural Networks (CNNs) have rapidly evolved since their neuroscience beginnings. These models efficiently and accurately classify images by optimizing the model’s hidden representations to these images through training. These representa- tions have been shown to resemble neural data...