Effects of target-amplitude and background-contrast uncertainty predicted by a normalized template-matching observer.
Effects of target-amplitude and background-contrast uncertainty predicted by a normalized template-matching observer.
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DOI：
10.1167/jov.23.12.8
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发表时间：
2023-10-04
影响因子：
1.8
通讯作者：
中科院分区：
文献类型：
--
作者：
在自然条件下检测目标时，视觉系统几乎总是面临多个同时存在的外部不确定性维度。研究了目标振幅和背景对比度同时存在的不确定性。这些维度对检测有很大的影响，并且在自然场景中变化很大。我们测量了人类在白噪声和自然场景背景下检测正弦波目标的两级先验概率。我们推导并测试了理想的白噪声背景观测器，一个模板匹配观测器的特殊情况，它随背景对比度动态移动其标准（DTM观测器），以及两个具有固定标准的更简单模型：模板匹配（TM）观测器和规范化模板匹配（NTM）观测器，它通过背景对比度规范化模板响应。仿真结果表明，当目标先验较低时，NTM观测器的性能接近最优，而TM观测器的性能接近随机，这表明对目标先验的操纵对于模型之间的区分是有价值的。令人惊讶的是，我们发现NTM和DTM观察者比TM观察者更能解释人类在两种背景类型下的表现。我们认为，视觉系统最有可能利用对比度归一化，而不是动态准则调整，以处理同时背景对比度和目标幅度的不确定性。最后，我们的研究结果表明，在高不确定性水平下收集的数据具有丰富的结构，能够区分模型，为研究高维不确定性提供了另一种方法。
When detecting targets under natural conditions, the visual system almost always faces multiple, simultaneous, dimensions of extrinsic uncertainty. This study focused on the simultaneous uncertainty about target amplitude and background contrast. These dimensions have a large effect on detection and vary greatly in natural scenes. We measured the human performance for detecting a sine-wave target in white noise and natural-scene backgrounds for two levels of prior probability of the target being present. We derived and tested the ideal observer for white-noise backgrounds, a special case of a template-matching observer that dynamically moves its criterion with the background contrast (the DTM observer) and two simpler models with a fixed criterion: the template-matching (TM) observer and the normalized template-matching (NTM) observer that normalizes template response by background contrast. Simulations show that, when the target prior is low, the performance of the NTM observer is near optimal and the TM observer is near chance, suggesting that manipulating the target prior is valuable for distinguishing among models. Surprisingly, we found that the NTM and DTM observers better explain human performance than the TM observer for both target priors in both background types. We argue that the visual system most likely exploits contrast normalization, rather than dynamic criterion adjustment, to deal with simultaneous background contrast and target amplitude uncertainty. Finally, our findings show that the data collected under high levels of uncertainty have a rich structure capable of discriminating between models, providing an alternative approach for studying high dimensions of uncertainty.
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影响因子：
2.5
作者：
Cavanaugh, JR;Bair, W;Movshon, JA
通讯作者：
Movshon, JA
影响因子：
1.8
作者：
Eckstein, Miguel P.
通讯作者：
Eckstein, Miguel P.
DOI：
10.1364/josaa.1.000900
发表时间：
1984-01-01
影响因子：
1.9
作者：
BURGESS, A;GHANDEHARIAN, H
通讯作者：
GHANDEHARIAN, H
影响因子：
1.8
作者：
Cavanagh, Patrick;Anstis, Stuart
通讯作者：
Anstis, Stuart
影响因子：
3.8
作者：
Bochud, FO;Abbey, CK;Eckstein, MP
通讯作者：
Eckstein, MP