Automating the Hunt for Volcanoes on Venus

Our long-term goal is to develop a trainable tool for locating patterns of interest in large image databases. Toward this goal we have developed a prototype system, based on classical filtering and statistical pattern recognition techniques, for automatically locating volcanoes in the Magellan SAR database of Venus. Training for the specific volcano-detection task is obtained by synthesizing feature templates (via normalization and principal components analysis) from a small number of examples provided by experts. Candidate regions identified by a focus of attention (FOA) algorithm are classified based on correlations with the feature templates. Preliminary tests show performance comparable to trained human observers

THE ROLE OF ALTERNATIVE AGRICULTURAL ENTERPRISES IN A CHANGING AGRICULTURAL ECONOMY

Agribusiness,

Finding Faces in Cluttered Scenes using Random Labeled Graph Matching

An algorithm for locating quasi-frontal views of human faces in cluttered scenes is presented. The algorithm works by coupling a set of local feature detectors with a statistical model of the mutual distances between facial features it is invariant with respect to translation, rotation (in the plane), and scale and can handle partial occlusions of the face. On a challenging database with complicated and varied backgrounds, the algorithm achieved a correct localization rate of 95% in images where the face appeared quasi-frontally

Automated analysis of radar imagery of Venus: handling lack of ground truth

Lack of verifiable ground truth is a common problem in remote sensing image analysis. For example, consider the synthetic aperture radar (SAR) image data of Venus obtained by the Magellan spacecraft. Planetary scientists are interested in automatically cataloging the locations of all the small volcanoes in this data set; however, the problem is very difficult and cannot be performed with perfect reliability even by human experts. Thus, training and evaluating the performance of an automatic algorithm on this data set must be handled carefully. We discuss the use of weighted free-response receiver-operating characteristics (wFROCs) for evaluating detection performance when the “ground truth” is subjective. In particular, we evaluate the relative detection performance of humans and automatic algorithms. Our experimental results indicate that proper assessment of the uncertainty in “ground truth” is essential in applications of this nature

Face Localization via Shape Statistics

In this paper, a face localization system is proposed in which local detectors are coupled with a statistical model of the spatial arrangement of facial features to yield robust performance. The outputs from the local detectors are treated as candidate locations and constellations are formed from these. The effects of translation, rotation, and scale are eliminated by mapping to a set of shape variables. The constellations are then ranked according to the likelihood that the shape variables correspond to a face versus an alternative model. Incomplete constellations, which occur when some of the true features are missed, are handled in a principled way

Tessellations and Pattern Formation in Plant Growth and Development

The shoot apical meristem (SAM) is a dome-shaped collection of cells at the apex of growing plants from which all above-ground tissue ultimately derives. In Arabidopsis thaliana (thale cress), a small flowering weed of the Brassicaceae family (related to mustard and cabbage), the SAM typically contains some three to five hundred cells that range from five to ten microns in diameter. These cells are organized into several distinct zones that maintain their topological and functional relationships throughout the life of the plant. As the plant grows, organs (primordia) form on its surface flanks in a phyllotactic pattern that develop into new shoots, leaves, and flowers. Cross-sections through the meristem reveal a pattern of polygonal tessellation that is suggestive of Voronoi diagrams derived from the centroids of cellular nuclei. In this chapter we explore some of the properties of these patterns within the meristem and explore the applicability of simple, standard mathematical models of their geometry.Comment: Originally presented at: "The World is a Jigsaw: Tessellations in the Sciences," Lorentz Center, Leiden, The Netherlands, March 200

Inferring individual attributes from search engine queries and auxiliary information

Internet data has surfaced as a primary source for investigation of different aspects of human behavior. A crucial step in such studies is finding a suitable cohort (i.e., a set of users) that shares a common trait of interest to researchers. However, direct identification of users sharing this trait is often impossible, as the data available to researchers is usually anonymized to preserve user privacy. To facilitate research on specific topics of interest, especially in medicine, we introduce an algorithm for identifying a trait of interest in anonymous users. We illustrate how a small set of labeled examples, together with statistical information about the entire population, can be aggregated to obtain labels on unseen examples. We validate our approach using labeled data from the political domain. We provide two applications of the proposed algorithm to the medical domain. In the first, we demonstrate how to identify users whose search patterns indicate they might be suffering from certain types of cancer. In the second, we detail an algorithm to predict the distribution of diseases given their incidence in a subset of the population at study, making it possible to predict disease spread from partial epidemiological data

A visual category filter for Google images

We extend the constellation model to include heterogeneous parts which may represent either the appearance or the geometry of a region of the object. The pans and their spatial configuration are learnt simultaneously and automatically, without supervision, from cluttered images. We describe how this model can be employed for ranking the output of an image search engine when searching for object categories. It is shown that visual consistencies in the output images can be identified, and then used to rank the images according to their closeness to the visual object category. Although the proportion of good images may be small, the algorithm is designed to be robust and is capable of learning in either a totally unsupervised manner, or with a very limited amount of supervision. We demonstrate the method on image sets returned by Google's image search for a number of object categories including bottles, camels, cars, horses, tigers and zebras

Progress in use of carbon-black-polymer composite vapor detector arrays for land mine detection

Thin films of carbon black-organic polymer composites have been deposited across two metallic leads, with swelling- induced resistance changes of the films signaling the presence of vapors. To identify and classify vapors, arrays of such vapor sensing elements have been constructed. Each element contained a different organic polymer as the insulating phase. The differing gas-solid partition coefficients for the various polymers of the detector array produced a pattern of resistance changes that was used to classify vapors and vapor mixtures. The performance of this system towards DNT, the predominant signature in the vapor phase above land miens, has been evaluated in detail, with robust detection demonstrated in the laboratory in less than 5 s in air at DNT levels in the low ppb range

Research Reports From Status Report: Identification of Appropriate Standards for Corrective Action for a Release from Petroleum Underground Storage Tanks

This document is a collection of research reports: Cost of Closure and Remediation for Petroleum Underground Storage Tanks Assessment of Number and Distribution of USTs Analysis of Potable Water Sources in Kentucky Analysis of Well Data and Soil Parameters as Related to the STATSGO Kentucky General Soil Map Petroleum Products: Chemical Composition, Tocxicological and Environmental Data Health Risk Analysis for Selected Petroleum Compounds Summary of Analytical Methods Soil Volume Calculations for UST Installations Generic Organic Containment Pathway Analysis for Components of Petroleum in Soil and Groundwate