Research on Visual Target Detection. Part I. Development of an Air-to-Ground Detection/Identification Model

Franklin, Margaret E.; Whittenburg, John A.

doi:10.21236/ad0619275

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…The second half of this statement is consistent with Whlttenburg's statement in a recent report (3): that although size has not been systematically investigated In field studies, the results generally indicate that detection probability is highest for larger vehicles, such as tanks, and lowest for small targets, such as single infantry personnel. However, it does appear that target size and target shape may interact under some circumstances so that the largest target in an array may not always have the highest detection probability.…”

Section: ) 2200supporting

confidence: 87%

A Field Survey of Air-to-Ground Target-Detection Problems

Hicks¹,

Moler²

1966

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Section: ) 2200supporting

confidence: 87%

A Field Survey of Air-to-Ground Target-Detection Problems

Hicks¹,

Moler²

1966

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“…Several attempts to develop mathematical models of air-to-ground target recognition performance have recently been made (Gilmour and Emerson, 1965;Franklin and Whittenburg, 1965;and Ornstein, Brainard, and Bishop, 196 1). Two major problems exist in attempting to validate existing models.…”

Section: Introductionmentioning

confidence: 99%

Experimental Evaluation of a Visual Detection Model

Greening

Wyman

1970

Hum Factors

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A fixed-base simulation experiment was performed to gather visual air-to-ground target recognition performance data for comparison with predictions from the Autonetics Detection Model. Color motion picture imagery obtained during a low-altitude fright was used to simulate the observer's forward view. Observer performance was measured in terms of probability and range of correct target recognition. The Autonetics Detection Model incorporates parameters related to the target, the environment, and the observer. In generating theoretical predictions from the model, values of all parameters were specified independently of the data obtained in the experiment. No curve fitting techniques were used to improve the fit between the empirical and theoretical curves. Results indicated a close relationship between the obtained performance data and the model predictions. A product-moment correlation of +0.53, significant at the 0,001 level, was obtained between the empirical and theoretical 50% recognition ranges. INTRODUCTIONSeveral attempts to develop mathematical models of air-to-ground target recognition performance have recently been made (Gilmour and Emerson, 1965;Franklin and Whittenburg, 1965; and Ornstein, Brainard, and Bishop, 196 1). Two major problems exist in attempting to validate existing models. First, the lack of empirical performance data obtained under controlled conditions precludes comparisons of actual performances with theoretical model predictions over a substantial range of parameter values. Second, the large number of model parameters requires quantitative specification of many variables which are difficult to measure accurately.As a result, much model validation work has been forced into one of two paths. Either the model is simplified to the extent that it is no longer applicable to operational problems, or the data used to test the model arise from simplified experimental conditions. This paper presents a preliminary attempt to evaluate the Autonetics Detection Model. It was felt that the simulation method used for obtaining empirical data in this study would preserve sufficient "real-world'' detail in target and background parameters while retaining experimental control so that all model parameters could be quantitatively specified. THE AUTONETICS DETECTION MODEL Statement of the ModelThe objective of the visual detection and recognition model utilized by Autonetics is to furnish an estimate of the cumulative probability of having recognized a target by a certain point in the target approach. This estimate is to be made on the basis of measurable characteristics of the target and its background, the environment, and the observer. The model is largely descriptive rather than rational, in that the formulation of the model is fitted to the form of existing experimental data on several aspects of the search process without serious consideration of the underlying neurological mechanisms.Basically, the cumulative probability is obtained as a product of a series of single glimpse probabilities according ...

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Mathematical Modeling of Air-to-Ground Target Acquisition

Greening

1976

Hum Factors

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Six principal models of air-to-ground target acquisition modeling and prediction are described in a common format and are compared in terms of structure, types o f submodels, unique features, and evidence of validity. Sensitivity to variables is examined semiquantitatively. Most o f the models share certain features, such as (1) strong emphasis on purely optical elements of target acquisition with corresponding neglect of cognitive factors, (2) reliance on laboratory dara rather than field data for sources of submodels, and (3) limited evidence o f overall validation. The implications of the characteristics of existing models for current applications and for possible future work are discussed.

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Research on Visual Target Detection. Part I. Development of an Air-to-Ground Detection/Identification Model

Cited by 4 publications

References 9 publications

A Field Survey of Air-to-Ground Target-Detection Problems

A Field Survey of Air-to-Ground Target-Detection Problems

Experimental Evaluation of a Visual Detection Model

Mathematical Modeling of Air-to-Ground Target Acquisition

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