Engineering topics

Wandell, Brian A.

Publications and source records attributed to Wandell, Brian A..

12 records

NASA NTRS1997

Center of Excellence in Model-Based Human Performance

The Center of Excellence (COE) was created in 1984 to facilitate active collaboration between the scientists at Ames Research Center and the Stanford Psychology Department. As this document will review, over that period of time, the COE served its function well. Funds from the Center supported a large number of projects over the last ten years. Many of the people who were supported by the Center Have gone on to distinguished research careers in government, industry and university. In fact, several of the people currently working at NASA Ames were initially funded by the Center mechanism, which served as a useful vehicle for attracting top quality candidates and supporting their research efforts. We are grateful for NASA's support over the years. As we reviewed in the reports for each year, the COE budget generally provided a portion of the true costs of the individual research project. Hence, the funds from the COE were leveraged with funds from industry and other government agencies. In this way, we feel that all parties benefitted greatly from the collaborative spirit and interactive aspects of the COE. The portion of the support from NASA was particularly important in helping members of the COE to set aside the time to publish papers and communicate advances in our understanding of human performance in NASA-related missions.

Wandell, Brian A.↗

NASA NTRS1997

Center of Excellence in Model-Based Human Performance

The Center of Excellence (COE) was created in 1984 to facilitate active collaboration between the scientists at Ames Research Center and the Stanford Psychology Department. As this document will review, over that period of time, the COE served its function well. Funds from the Center supported a large number of projects over the last ten years. Many of the people who were supported by the Center have gone on to distinguished research careers in government, industry and university. In fact, several of the people currently working at NASA Ames were initially funded by the Center mechanism, which served as a useful vehicle for attracting top quality candidates and supporting their research efforts. We are grateful for NASA's support over the years. As we reviewed in the reports for each year, the COE budget generally provided a portion of the true costs of the individual research projects. Hence, the funds from the COE were leveraged with funds from industry and other government agencies. In this way, we feel that all parties benefitted greatly from the collaborative spirit and interactive aspects of the COE. The portion of the support from NASA was particularly important in helping members of the COE to set aside the time to publish papers and communicate advances in our understanding of human performance in NASA-related missions.

Wandell, Brian A.↗

NASA NTRS1993

Overview of research in progress at the Center of Excellence

The Center of Excellence (COE) was created nine years ago to facilitate active collaboration between the scientists at Ames Research Center and the Stanford Psychology Department. Significant interchange of ideas and personnel continues between Stanford and participating groups at NASA-Ames; the COE serves its function well. This progress report is organized into sections divided by project. Each section contains a list of investigators, a background statement, progress report, and a proposal for work during the coming year. The projects are: Algorithms for development and calibration of visual systems, Visually optimized image compression, Evaluation of advanced piloting displays, Spectral representations of color, Perception of motion in man and machine, Automation and decision making, and Motion information used for navigation and control.

Wandell, Brian A.↗

NASA NTRS1990

Task-dependent color discrimination

When color video displays are used in time-critical applications (e.g., head-up displays, video control panels), the observer must discriminate among briefly presented targets seen within a complex spatial scene. Color-discrimination threshold are compared by using two tasks. In one task the observer makes color matches between two halves of a continuously displayed bipartite field. In a second task the observer detects a color target in a set of briefly presented objects. The data from both tasks are well summarized by ellipsoidal isosensitivity contours. The fitted ellipsoids differ both in their size, which indicates an absolute sensitivity difference, and orientation, which indicates a relative sensitivity difference.

Poirson, Allen B.↗

NASA NTRS1990

Surface characterizations of color threshold

The paper evaluates how well three different parametric shapes, ellipsoids, rectangles, and parallelograms, serve as models of three-dimentional detection contours. The constraints of the procedures for deriving the best-fitting shapes on inferences about the theoretical visual detection mechanisms are described. Results of two statistical tests show that only the parallelogram fits the data with more precision than the variance in repeated threshold measurements, and thus provides a slightly better fit than the other two shapes. Nevertheless it does not serve as a better guide than the ellipsoidal model for interpolating from the measurements to thresholds in novel color directions.

Poirson, Allen B.↗

NASA NTRS1990

Stanford/NASA-Ames Center of Excellence in model-based human performance

The human operator plays a critical role in many aeronautic and astronautic missions. The Stanford/NASA-Ames Center of Excellence in Model-Based Human Performance (COE) was initiated in 1985 to further our understanding of the performance capabilities and performance limits of the human component of aeronautic and astronautic projects. Support from the COE is devoted to those areas of experimental and theoretical work designed to summarize and explain human performance by developing computable performance models. The ultimate goal is to make these computable models available to other scientists for use in design and evaluation of aeronautic and astronautic instrumentation. Within vision science, two topics have received particular attention. First, researchers did extensive work analyzing the human ability to recognize object color relatively independent of the spectral power distribution of the ambient lighting (color constancy). The COE has supported a number of research papers in this area, as well as the development of a substantial data base of surface reflectance functions, ambient illumination functions, and an associated software package for rendering and analyzing image data with respect to these spectral functions. Second, the COE supported new empirical studies on the problem of selecting colors for visual display equipment to enhance human performance in discrimination and recognition tasks.

Wandell, Brian A.↗

NASA NTRS1989

Standard surface-reflectance model and illuminant estimation

A vector analysis technique was adopted to test the standard reflectance model. A computational model was developed to determine the components of the observed spectra and an estimate of the illuminant was obtained without using a reference white standard. The accuracy of the standard model is evaluated.

Tominaga, Shoji↗

NASA NTRS1989

Black light - How sensors filter spectral variation of the illuminant

Visual sensor responses may be used to classify objects on the basis of their surface reflectance functions. In a color image, the image data are represented as a vector of sensor responses at each point in the image. This vector depends both on the surface reflectance functions and on the spectral power distribution of the ambient illumination. Algorithms designed to classify objects on the basis of their surface reflectance functions typically attempt to overcome the dependence of the sensor responses on the illuminant by integrating sensor data collected from multiple surfaces. In machine vision applications, it is shown that it is often possible to design the sensor spectral responsivities so that the vector direction of the sensor responses does not depend upon the illuminant. The conditions under which this is possible are given and an illustrative calculation is performed. In biological systems, where the sensor responsivities are fixed, it is shown that some changes in the illumination cause no change in the sensor responses. Such changes in illuminant are called black illuminants. It is possible to express any illuminant as the sum of two unique components. One component is a black illuminant. The second component is called the visible component. The visible component of an illuminant completely characterizes the effect of the illuminant on the vector of sensor responses.

Brainard, David H.↗

NASA NTRS1988

Discrete analysis of spatial-sensitivity models

Procedures for reducing the computational burden of current models of spatial vision are described, the simplifications being consistent with the prediction of the complete model. A method for using pattern-sensitivity measurements to estimate the initial linear transformation is also proposed which is based on the assumption that detection performance is monotonic with the vector length of the sensor responses. It is shown how contrast-threshold data can be used to estimate the linear transformation needed to characterize threshold performance.

Nielsen, Kenneth R. K.↗

NASA NTRS1987

Computational models of human vision with applications

The research program supported by this grant was initiated in l977 by the Joint Institute for Aeronautics and Acoustics of the Department of Aeronautics and Astronautics at Stanford University. The purpose of the research was to study human performance with the goal of improving the design of flight instrumentation. By mutual agreement between the scientists at NASA-Ames and Stanford, all research activities in this area were consolidated into a single funding mechanism, NCC 2-307 (Center of Excellence Grant, 7/1/84 - present). This is the final report on this research grant.

Wandell, Brian A.↗

NASA NTRS1987

The synthesis and analysis of color images

A method is described for performing the synthesis and analysis of digital color images. The method is based on two principles. First, image data are represented with respect to the separate physical factors, surface reflectance and the spectral power distribution of the ambient light, that give rise to the perceived color of an object. Second, the encoding is made efficiently by using a basis expansion for the surface spectral reflectance and spectral power distribution of the ambient light that takes advantage of the high degree of correlation across the visible wavelengths normally found in such functions. Within this framework, the same basic methods can be used to synthesize image data for color display monitors and printed materials, and to analyze image data into estimates of the spectral power distribution and surface spectral reflectances. The method can be applied to a variety of tasks. Examples of applications include the color balancing of color images, and the identification of material surface spectral reflectance when the lighting cannot be completely controlled.

Wandell, Brian A.↗

NASA NTRS1986

Color rendering of color camera data

Conditions under which a computational procedure can be applied to arbitrary camera sensors to permit estimation of the human photoreceptor response are considered. The adopted procedures recover the effective surface reflectance at the time of measurement, and the reflectance estimates depend not only on the surface, but upon the viewing geometry. The present method for color rendering assumes that the observer's state of adaptation at the time of viewing the original and the rendered images is the same. The analysis aids in specifying which classes of surfaces are required to be accurately rendered, and for which surfaces some error can be tolerated.

Wandell, Brian A.↗