Combined 3-D auditory-visual cueing for a visual target acquisition task

2007 ◽  
Author(s):  
Rachael L. Westergren ◽  
Paul R. Havig ◽  
Eric L. Heft
Keyword(s):  
Visual Target ◽  
Target Acquisition ◽  
Visual Cueing ◽  
Acquisition Task

Spatial Multisensory Cueing to Support Visual Target-Acquisition Performance

2012 ◽  
Vol 56 (1) ◽  
pp. 1312-1316 ◽  
Author(s):  
Julio C. Mateo ◽  
Brian D. Simpson ◽  
Robert H. Gilkey ◽  
Nandini Iyer ◽  
Douglas S. Brungart
Keyword(s):  
Visual Target ◽  
Target Acquisition ◽  
Acquisition Performance

Differential Effects of ‘Noise’ Stress and Workload on Salience and Hemispace Bias in a Screen-Based Target Acquisition Task

1995 ◽  
Vol 39 (13) ◽  
pp. 864-867
Author(s):  
Alan F. Stokes ◽  
James A. Pharmer ◽  
Aysenil Belger
Keyword(s):  
Individual Differences ◽  
Stress Condition ◽  
Target Selection ◽  
Attentional Biases ◽  
Target Acquisition ◽  
Differential Effects ◽  
Noise Stress ◽  
Acquisition Task ◽  
High Bias ◽  
Related Stress

Attentional biases in stressed or overworked radar operators (airborne or in Combat Information Centers, etc.) may have important operational implications. This study examined the effects of workload and non-workload-related stress on salience bias in a screen-based target selection and engagement task. Results in the control condition confirmed that appreciable baseline salience bias existed. Moreover, in the non-task-related stress condition (noise/anxiety), a significant increase in salience bias was observed. Elevated workload, in contrast, was associated with no significant changes in salience bias. Overall, the results showed stable individual differences in salience bias and suggested that non-workload related stress influenced ‘high bias’ individuals proportionately more than ‘low bias’ individuals-an outcome with potential implications for selection. Subjects were also significantly biased toward the left hemispace, a powerful effect that remained even after the experiment was repeated using subjects’ left instead of right hands.

Visual Target Acquisition: Bridging the Gap from Vision Research to Applied Models

1992 ◽  
Vol 36 (18) ◽  
pp. 1418-1419
Author(s):  
Theodore J. Doll
Keyword(s):  
Vision Research ◽  
Visual Target ◽  
Lessons Learned ◽  
The Other ◽  
Bad News ◽  
Good News ◽  
Target Acquisition ◽  
Ground Vehicles ◽  
Desert Storm ◽  
Highly Effective

One of the lessons learned in Desert Storm is that visual and electro-optical (VISEO) systems are highly effective. Most of us recall seeing CNN footage of EO sensors acquiring targets and guiding weapons to destroy the target. The effectiveness of VISEO systems is the good news. The bad news is that the other side is likely to be equipped with similar VISEO systems in the next war. Our personnel and materiel are therefore likely to be highly vulnerable to such systems in future conflicts. There is an urgent need to make our weapons systems, especially ground vehicles, less conspicuous on the battlefield, i.e., to develop more effective camouflage and signature suppression techniques.

Development of a Control Theoretic Alternative to Fitts’ Law With Application to In-Vehicle Touchscreen Interface

2015 ◽  
Author(s):  
Chao Wang ◽  
Bahram Ravani
Keyword(s):  
Physical Interpretation ◽  
Model Identification ◽  
Human Operator ◽  
Target Acquisition ◽  
Relative Movement ◽  
Brief Treatment ◽  
Fitts Law ◽  
Proposed Model ◽  
Acquisition Task

A control theoretic alternative to Fitts’ Law based on a modified crossover model is proposed. A physical interpretation of the model offers the unification of various different formulations of Fitts’ Law. Model identification and validation is carried out for a target acquisition task using a touchscreen. A brief treatment of noise generated by random relative movement between the human operator and the touchscreen (such as in-vehicle touchscreen based devices) is considered using the proposed model.

Controlling Contrast in Target Acquisition Simulations Involving Complex Backgrounds

1992 ◽  
Vol 36 (18) ◽  
pp. 1435-1439
Author(s):  
William Kosnik
Keyword(s):  
Simple Technique ◽  
Visual Target ◽  
Systematic Effect ◽  
Target Acquisition ◽  
Low Contrast ◽  
Performance Factors ◽  
Background Structure ◽  
Inherent Feature ◽  
Uniform Background ◽  
Natural Terrain

Visual target acquisition (TA) often involves detecting targets against natural backgrounds that have complex luminance distributions. The purpose of this study was to evaluate a simple technique that controls target contrast in the presence of varying backgrounds. Target contrast was measured by the root mean square (rms) method and was controlled by adjusting only the target luminance, leaving the background unchanged. The technique was tested in a TA paradigm in which observers searched for an aircraft that was embedded in 1) a uniform background, 2) a natural terrain background, or 3) a moving natural terrain background. Four target contrast levels were tested. The results showed that TA time varied with background and target contrast. Significant differences in TA time were observed among the different backgrounds for targets of the same physical contrast, especially at low contrast levels. Although contrast had a systematic effect on TA performance, factors other than contrast influenced TA performance. It was concluded that background structure increased TA time by camouflaging targets and by introducing distractors to the task. Such an approach could be used to model TA performance under conditions where target and background complexity are an inherent feature of the TA task.

Visual Search and Detection in Background Clutter

1992 ◽  
Vol 36 (18) ◽  
pp. 1420-1424
Author(s):  
Theodore J. Doll ◽  
Shane W. McWhorter ◽  
David E. Schmieder
Keyword(s):  
Real World ◽  
Vision Research ◽  
Visual Target ◽  
Basic Research ◽  
Pattern Perception ◽  
Target Acquisition ◽  
Engineering Models ◽  
Background Clutter ◽  
Improved Model ◽  
Transfer Of Information

Two traditions of vision modeling have coexisted for many years with little or no transfer of information between them. Those interested in models of visual target acquisition for real-world scenarios have developed engineering models, which are essentially empirical summaries of visual performance data. On the other hand, basic researchers in visual psychophysics and neurophysiology have developed quantitative models of pattern perception. The basic research models have increased in generality and scope to the point that they are potentially powerful tools for addressing certain real-world needs that have recently come to the fore. The needs include quantitative, theory-based methods for evaluating target signatures, effects of background clutter, and observer false alarm rates. This paper reviews the shortcomings of existing target acquisition models, and reports work in progress to develop an improved model of target acquisition that incorporates a model of pattern perception from basic vision research.

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