Other Computer Sciences Commons^™

Context In Computer Vision: A Taxonomy, Multi-Stage Integration, And A General Framework, Xuan Wang

Dissertations, Theses, and Capstone Projects

Contextual information has been widely used in many computer vision tasks, such as object detection, video action detection, image classification, etc. Recognizing a single object or action out of context could be sometimes very challenging, and context information may help improve the understanding of a scene or an event greatly. However, existing approaches design specific contextual information mechanisms for different detection tasks.

In this research, we first present a comprehensive survey of context understanding in computer vision, with a taxonomy to describe context in different types and levels. Then we proposed MultiCLU, a new multi-stage context learning and utilization framework, …

Deep Learning-Based Human Action Understanding In Videos, Elahe Vahdani

Dissertations, Theses, and Capstone Projects

The understanding of human actions in videos holds immense potential for technological advancement and societal betterment. This thesis explores fundamental aspects of this field, including action recognition in trimmed clips and action localization in untrimmed videos. Trimmed videos contain only one action instance, with moments before or after the action excluded from the video. However, the majority of videos captured in unconstrained environments, often referred to as untrimmed videos, are naturally unsegmented. Untrimmed videos are typically lengthy and may encompass multiple action instances, along with the moments preceding or following each action, as well as transitions between actions. In the …

Machine Learning For Terminal Procedure Chart Change Detection, Anthony M. Marchiafava

University of New Orleans Theses and Dissertations

Terminal Procedure Charts are a constantly updated and necessary tool for aircraft personnel to approach and take off from airport runways safely. Detecting changes within these charts is a time-consuming and laborious process. Here machine learning techniques were used to predict regions of change in charts based on detecting the charts image regions and comparing features extracted from those regions. Outlined are methodologies to detect differences between two separate charts to produce images with changed regions clearly indicated. Both more conventional computer vision and machine learning techniques were applied. For images with minor shifts, the proposed model is able to …

Detection Of Mild Cognitive Impairment Using Diffusion Compartment Imaging, Matthew Jones

Master's Projects

The result of applying the Neurite Orientation Density and Dispersion Index (NODDI) algorithm to improve the prediction accuracy for patients diagnosed with MCI is reported. Calculations were carried out using a collection of 68 patients (34 control and 34 with MCI) gathered from the Alzheimer’s Disease Neuroimaging Initiative database (ADNI). Patient data includes the use of high-resolution Magnetic Resonance Images as with as Diffusion Tensor Imaging. A Linear Regression accuracy of 83% was observed using the added NODDI summary statistic: Orientation Dispersion Index (ODI). A statistically significant difference in groups was found between control patients and patients with MCI with …

Sports Analytics With Computer Vision, Colby T. Jeffries

Senior Independent Study Theses

Computer vision in sports analytics is a relatively new development. With multi-million dollar systems like STATS’s SportVu, professional basketball teams are able to collect extremely fine-detailed data better than ever before. This concept can be scaled down to provide similar statistics collection to college and high school basketball teams. Here we investigate the creation of such a system using open-source technologies and less expensive hardware. In addition, using a similar technology, we examine basketball free throws to see whether a shooter’s form has a specific relationship to a shot’s outcome. A system that learns this relationship could be used to …

Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto

Computer Engineering

The Underwater Computer Vision – Fish Recognition project includes the design and implementation of a device that can withstand staying underwater for a duration of time, take pictures of underwater creatures, such as fish, and be able to identify certain fish. The system is meant to be cheap to create, yet still able to process the images it takes and identify the objects in the pictures with some accuracy. The device can output its results to another device or an end user.

Geological Object Recognition In Extraterrestrial Environments, Gregory M. Elfers

Electronic Thesis and Dissertation Repository

On July 4 1997, the landing of NASA’s Pathnder probe and its rover Sojourner marked the beginning of a new era in space exploration; robots with the ability to move have made up the vanguard of human extraterrestrial exploration ever since. With Sojourners landing, for the rst time, a ground traversing robot was at a distance too far from earth to make direct human control practical. This has given rise to the development of autonomous systems to improve the e?ciency of these robots,in both their ability to move,and their ability to make decisions regarding their environment. Computer Vision comprises a …