With an increasing number of wireless applications at microwave frequencies, the frequency spectrum is becoming quite crowded. Due to this congestion, the current state of technology is leading towards upper microwave and millimeter wave spectra as they also offer other distinct advantages such as larger bandwidth and smaller component footprint....
This thesis consists of two major components. The first part is concerned with video object instance segmentation (VOS), which is the task of assigning per-pixel labels perframe of a video sequence to indicate foreground object instance membership, given the first frame ground truth mask. VOS has myriad applications, from video...
This report presents an efficient method for semi-supervised video object segmentation – the problem of identifying foreground pixels occupied by a target object. The target is specified by the ground-truth mask in the first video frame. While the state of the art achieves a segmentation accuracy greater than 80%, it...
With the increase in demand for streaming media capabilities across the Internet, the focus has shifted from traditional client-server to peer-to-peer approaches. Content Distribution Networks (CDNs) have also recently moved from web acceleration to media streaming. P2P CDNs can be used both as a delivery mechanism and as an independent...
While individual portfolio diversity analysis is a well-studied problem in visualization, the visual analysis of individual or groups of portfolios, over time, has received little attention. Such analysis, however, is important to researchers who are interested in better understanding portfolio management behavior of experts as well as novices. We conducted...
Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
Cold air pools are spatiotemporal phenomena that occur when cold air from higher elevations roll down the slope to accumulate in lower elevations. Behaviors like this lead to microclimate anomalies such as the city of Corvallis (Oregon) experiencing persistent cold weather even on a sunny day. We analyze multivariate temperature...
Transportation infrastructure provides a vital service for the functionality of a
city. The efficient design of road networks poses an interesting topic in computer
science for digital content developers. For civil engineers, the visualization of
analysis results on infrastructure both efficiently and intuitively is crucial. The
following contributions are made...
N-ary relationships, which relate N entities where N is not necessarily two, are omnipresent in real life. In this thesis, we develop a visualization technique for N-ary relationships.
First, we propose a visual metaphor that utilizes vertices and polygons to represent entities and N-ary relationships. Based on this visual metaphor,...
Open Source software gives users the freedom to copy, modify and redistribute source code without legal entanglements. The evolution of these software communities usually depend a lot on how the participating developers and users interact and co-operate with each other. Over the past few years, open source software have become...
Graphics hardware in mobile devices has become more powerful, allowing rendering techniques such as ray-cast volume rendering to be done at interactive rates. This increase of performance provides desktop capabilities combined with the portability of a tablet. Volumes can demand a high amount of memory in order to be loaded...
Uploading everyday information about food intake, sleep, number of steps and then generating consolidated peer visual reports for participants in large-scale health studies, often divided into multiple treatment groups, can be challenging.
This challenge is even bigger if subjects are young teenagers between the age of 14-19 active in sports,...
3D datasets acquire great importance in the context of medical imaging. In this thesis we survey and enhance solutions to problems inherently associated with 3D datasets-processing time,noise and visualization. Efforts include development of a tool kit to provide a multi-threaded processing platform to cut processing time, produce real time visualization...
Oftentimes in visualization, the goal of using volume datasets is not just to visualize them but also to analyze and compare them. In order to compare the two volumes, we cannot take all the voxels into consideration. The size of a typical volume data set is quite large (maybe a...
Realistic (ideally photorealistic) real-time rendering has remained an elusive goal in computer graphics. While photorealistic rendering has certainly been achieved at the expense of tremendous computational resources and corresponding rendering times; real-time rendering typically must accept a great number of compromises to achieve adequate performance, such as aliasing artifacts, the...
Approximate string matching is commonly used to align genetic sequences (DNA
or RNA) to determine their shared characteristics. In contrast with the standard
dynamic programming methods which use local edit distance models, the Walking
Tree heuristic method was created to handle non-local changes, e.g., translocations,
inversions, and duplications, altogether and...
Wave energy converter research continues to advance and new developers are continuing to emerge, leading to the need for a general modeling methodology. This work attempts to outline the design methodology necessary to perform frequency domain analysis on a generic wave energy converter. A two-body point absorber representing a generic...
In supervised learning, label information can be provided at different levels of granularity. For small datasets, it is possible to acquire a label for each data instance. However, in the big-data regime, this fine granularity approach is prohibitively costly. For example, in semi-supervised learning, only a limited number of samples...
Efficient time-series analysis can impact multiple application domains such as motif discovery in gene analysis or music data, extracting spectro-temporal patterns in acoustic scene analysis, or annotating and classifying electrical bio-signals (such as ECG, EEG, and EMG) for medical applications.
Time-series analysis involves a variety of tasks.
To predict future...
The thesis focuses on activity recognition from sensor data, which has spurred a great deal of interest due to its impact on health care and security. Previous work on activity recognition from multivariate time series data has mainly applied supervised learning techniques which require a high degree of annotation effort...