Engineering topics

Cheeseman, P.

Publications and source records attributed to Cheeseman, P..

8 records

NASA NTRS2004

Dramatic Improvements to Feature Based Stereo

The camera registration extracted from feature based stereo is usually considered sufficient to accurately localize the 3D points. However, for natural scenes the feature localization is not as precise as in man-made environments. This results in small camera registration errors. We show that even very small registration errors result in large errors in dense surface reconstruction. We describe a method for registering entire images to the inaccurate surface model. This gives small, but crucially important improvements to the camera parameters. The new registration gives dramatically better dense surface reconstruction.

Smelyansky, V. N.↗

NASA NTRS2001

(Almost) Featureless Stereo: Calibration and Dense 3D Reconstruction Using Whole Image Operations

The conventional approach to shape from stereo is via feature extraction and correspondences. This results in estimates of the camera parameters and a typically spare estimate of the surface. Given a set of calibrated images, a dense surface reconstruction is possible by minimizing the error between the observed image and the image rendered from the estimated surface with respect to the surface model parameters. Given an uncalibrated image and an estimated surface, the camera parameters can be estimated by minimizing the error between the observed and rendered images a function of the camera parameters. We use a very small dense set of matched features to provide camera parameter estimates for the initial dense surface estimate. We then re-estimate the camera parameters as described above, and then re-estimate the surface. This process is iterated. Whilst it can not be proven to converge, we have found that around three iterations results in excellent surface and camera parameters estimates.

Smelyanskiy, V. N.↗

NASA NTRS2000

Visualization, Extraction and Quantification of Discontinuities in Compressible Flows

Scientific visualizations of two-dimensional compressible flow of a gas with discontinuities are presented. The numerical analogue to experimental techniques such as schlieren imaging, shadowgraphs, and interferograms are discussed. Edge detection techniques are utilized to identify the discontinuities. In particular, the zero crossing of the Laplacian of a field (usually density) is recommended for extracting the discontinuities. An algorithm to extract and quantify the discontinuities is presented. To illustrate the methods developed in the report, the example chosen is that of an unsteady interaction of a shock wave with a contact discontinuity.

Samtaney, Ravi↗

NASA NTRS1998

Onboard Science Data Analysis: Opportunities, Benefits, and Effects on Mission Design

Much of the initial focus for spacecraft autonomy has been on developing new software and systems concepts to automate engineering functions of the spacecraft: guidance, navigation and control, fault protection, and resources management. However, the ultimate objectives of NASA missions are science objectives, which implies that we need a new framework for perfoming science data evaluation and observation planning autonomously onboard spacecraft.

spacecraft autonomy observation planning science d↗

NASA NTRS1995

The 11 Micron Emissions of Carbon Stars

A new classification scheme of the IRAS LRS carbon stars is presented. It comprises the separation of 718 probable carbon stars into 12 distinct self-similar spectral groupings. Continuum temperatures are assigned and range from 470 to 5000 K. Three distinct dust species are identifiable: SiC, alpha:C-H, and MgS. In addition to the narrow 11 + micron emission feature that is commonly attributed to SiC, a broad 11 + micron emission feature, that is correlated with the 8.5 and 7.7 micron features, is found and attributed to alpha:C-H. SiC and alpha:C-H band strengths are found to correlate with the temperature progression among the Classes. We find a spectral sequence of Classes that reflects the carbon star evolutionary sequence of spectral types, or alternatively developmental sequences of grain condensation in carbon-rich circumstellar shells. If decreasing temperature corresponds to increasing evolution, then decreasing temperature corresponds to increasing C/O resulting in increasing amounts of carbon rich dust, namely alpha:C-H. If decreasing the temperature corresponds to a grain condensation sequence, then heterogeneous, or induced nucleation scenarios are supported. SiC grains precede alpha:C-H and form the nuclei for the condensation of the latter material. At still lower temperatures, MgS appears to be quite prevalent. No 11.3 micron PAH features are identified in any of the 718 carbon stars. However, one of the coldest objects, IRAS 15048-5702, and a few others, displays an 11.9 micron emission feature characteristic of laboratory samples of coronene. That feature corresponds to the C-H out of plane deformation mode of aromatic hydrocarbon. This band indicates the presence of unsaturated, sp(sup 3), hydrocarbon bonds that may subsequently evolve into saturated bonds, sp(sup 2), if, and when, the star enters the planetary nebulae phase of stellar evolution. The effusion of hydrogen from the hydrocarbon grain results in the evolution in wavelength of this 11.9 micron emission feature to the 11.3 micron feature.

Goebel, J. H.↗

NASA NTRS1995

The 11 Micron Emissions of Cabon Stars

A new classification scheme of the IRAS LRS carbon stars is presented. It comprises the separation of 718 probable carbon stars into 12 distinct self-similar spectral groupings. Continuum temperatures are assigned and range from 470 to 5000 K. Three distinct dust species are identifiable: SiC, alpha:C-H, and MgS. In addition to the narrow 11 + micron emission feature that is commonly attributed to SiC, a broad 11 + micron emission feature, that is correlated with the 8.5 and 7.7 micron features, is found and attributed to alpha:C-H. SiC and alpha:C-H band strengths are found to correlate with the temperature progression among the Classes. We find a spectral sequence of Classes that reflects the carbon star evolutionary sequence of spectral types, or alternatively developmental sequences of grain condensation in carbon-rich circumstellar shells. If decreasing temperature corresponds to increasing evolution, then decreasing temperature corresponds to increasing CIO resulting in increasing amounts of carbon rich dust, namely alpha:C-H. If decreasing the temperature corresponds to a grain condensation sequence, then heterogeneous, or induced nucleation scenarios are supported. SiC grains precede alpha:C-H and form the nuclei for the condensation of the latter material. At still lower temperatures, MgS appears to be quite prevalent. No 11.3 micron PAH features are identified in any of the 718 carbon stars. However, one of the coldest objects, IRAS 15048-5702, and a few others, displays an 11.9 micron emission feature characteristic of laboratory samples of coronene. That feature corresponds to the C-H out of plane deformation mode of aromatic hydrocarbon. This band indicates the presence of unsaturated, sp(sup 3), hydrocarbon bonds that may subsequently evolve into saturated bonds, sp(sup 2), if, and when, the star enters the planetary nebulae phase of stellar evolution. The effusion of hydrogen from the hydrocarbon grain results in the evolution in wavelength of this 11.9 micron emission feature to the 11.3 micron feature.

Goebel, J. H.↗

NASA NTRS1989

A Bayesian classification of the IRAS LRS Atlas

The availability of a reclassification of the IRAS LRS Atlas of spectra using a new Bayesian classification procedure (AutoClass) is announced. The classes of objects which result from the application of the AutoClass algorithm include many of the previously known LRS classes. New classes which have interesting astronomical and astrophysical interpretations were also found. Techniques, such as the AutoClass algorithm, have a bright future in the arena of astronomical classification problems.

Goebel, J.↗

NASA NTRS1986

Introduction to artificial intelligence

This paper presents an introductory view of Artificial Intelligence (AI). In addition to defining AI, it discusses the foundations on which it rests, research in the field, and current and potential applications.

Cheeseman, P.↗