In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...
This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of one or more targets in the image sequence. This is a very challenging task as algorithms need to deal with problems such as appearance variations,...
The widespread use of wireless devices that we have recently been witnessing, such as smartphones, tablets, laptops, and wirelessly accessible devices in general, is causing an unprecedented growth in the required amount of the wireless radio spectrum. On the other hand, the spectrum resource has, for the last several decades,...
This research explores several novel approaches to improve visualization and segmentation
of point clouds acquired with 3D laser scanning. 3D laser scanning is used
in a wide variety of applications including surveying and mapping, transportation asset
management, facilities management, building information modeling, crime scene investigations,
cultural heritage and geologic instigations....
Protein-protein interactions underlie all biological processes and are a field of study that has wide implications throughout many other fields including medicine, genetics, biology, and ecology. Proteins are the building blocks and primary actors of life. They work together to accomplish virtually every task within a cell, including, metabolism, signal...
We consider two semiparametric regression models for data analysis, the stochastic additive model (SAM) for nonlinear time series data and the additive coefficient model (ACM) for randomly sampled data with nonparametric structure. We employ the SCAD-penalized polynomial spline estimation method for estimation and simultaneous variable selection in both models. It...
In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
The quality of a digital image pipeline relies greatly on its color reproduction which should at a minimum handle the color constancy, and the final judgment of the excellence of the pipeline is made through subjective observations by humans.
This dissertation addresses a few topics surrounding the color processing of...