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Background Cancer genomics projects are producing ever-increasing amounts of rich and diverse data from patient samples. The ability to easily visualize this data in an integrated an intuitive way is currently limited by the current software available. As a result, users typically must use several different tools to view the different data types for their cohort, making it difficult to have a simple...
The Virtual Watershed Client, built using the Unity game engine, provides a tool that allows researchers, students, and others to observe and analyze geospatial datasets and theoretical model data acquired from the Virtual Watershed Platform. The Virtual Watershed Platform is used as a service to acquire data that is used by the Virtual Watershed Client to create terrain, satellite imagery, shapes,...
This paper presents a novel architecture for a classification system based on the visual saliency of images. The work is motivated by the difficulty of reviewing large numbers of images as a human operator in the context of Autonomous Underwater Vehicle (AUV) surveys. We formulate a feature space in which an algorithm operates over color and texture to determine saliency and illustrate how this can...
A robust inverse optimal adaptive visual servo controller is described that asymptotically regulates a camera's pose to a desired pose despite uncertainty in the time-varying distance from the camera to the target and parametric uncertainty in the camera calibration matrix. A high gain robust inverse optimal controller asymptotically stabilizes the rotation error system, whereas, an inverse optimal...
We present a technique for the integration of data from a ship based multibeam along with multibeam and stereo images gathered from an AUV. The novelty of the proposed technique is the ability to integrate data-sets at different resolutions to produce one consistent model that captures not only high resolution images of the seafloor but sweeping geological features that span kilometers.
We propose semantic texton forests, efficient and powerful new low-level features. These are ensembles of decision trees that act directly on image pixels, and therefore do not need the expensive computation of filter-bank responses or local descriptors. They are extremely fast to both train and test, especially compared with k-means clustering and nearest-neighbor assignment of feature descriptors...
The registration and 3D mosaicing of range images presents an interesting challenge for the underwater domain. This work attempts to lay out some of the issues involved in generating large 3D reconstructions of the benthos from two distinct views gathered from an AUV. Specifically, we address using 3D feature correspondence to estimate a Euclidean transformation between views and then refine that...
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