Pattern Recognition and Display Characteristics

W. R. Bush, R. B. Kelly, V. M. Donahue
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引用次数: 2

Abstract

This paper reports experimental results of human operator performance in a visual recognition task. The work began with a method of generating families of complex patterns to simulate certain characteristics of visual sensor displays, such as radar and infrared returns. The experimental effort was directed toward establishing criteria for predicting human operator performance in a map matching task. The operators' task was to recognize which of four patterns presented simultaneously with a reference pattern belonged to the reference pattern family. The measure of performance was the time in seconds taken by the operator to make a selection. Response times were more rapid when the reference pattern was less complex than the comparison than when the reference pattern was the more complex. Analysis of the display characteristics led to the selection of four physical measures to be used in predicting operator performance. These measures?pattern length, pattern density, and two measures of pattern complexity?correlated highly with response time, were not highly intercorrelated, and were applicable to natural sensor returns. The four measures were found to account for a high degree of the total variance. Regression equations were derived which predict performance from known values of the four measures.
模式识别和显示特性
本文报道了人类操作员在视觉识别任务中的表现的实验结果。这项工作开始于一种生成复杂图案家族的方法,以模拟视觉传感器显示的某些特征,如雷达和红外回波。实验的目的是建立预测人类操作员在地图匹配任务中的表现的标准。操作员的任务是识别与参考模式同时出现的四种模式中哪一种属于参考模式族。性能的衡量标准是以秒为单位的操作人员进行选择的时间。当参考模式较复杂时,响应时间比参考模式较复杂时更快。通过对显示特性的分析,选择了四种用于预测操作员性能的物理指标。这些措施?模式长度、模式密度和模式复杂度的两个度量?与响应时间高度相关,不高度相关,适用于自然传感器返回。研究发现,这四种测量方法在很大程度上解释了总方差。推导了回归方程,从已知的四个测量值预测性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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