通过模式特征检测二进制序列中的视觉纹理模式
Maria F Dal Martello1,2,3, Keiji Ota2,4,5,6, Dana E Pietralla2,7,8
1Dipartmento di Psicologia Generale, Università di Padova, Padova, Italy.
Journal of vision
|November 1, 2023
概括
人类观察者对检测被破坏的马尔科夫序列 (DMS) 纹理模式的敏感性有限. 性能明显低于最佳贝叶斯观察者,这表明依赖于特定的序列特征而不是整个模式.
科学领域:
- 认知心理学 认知心理学
- 感知科学是感知科学.
- 计算神经科学是一种计算神经科学.
背景情况:
- 人类感知到视觉纹理和图案.
- 信号检测理论量化了感知表现.
- 马尔科夫序列模型的顺序依赖关系.
研究的目的:
- 测量人类在信号检测任务中检测纹理模式的能力.
- 将人类的表现与最佳贝叶斯观察者的表现进行比较.
- 识别影响人类纹理模式检测的特征.
主要方法:
- 观察者将随机序列与被破坏的马尔科夫序列 (DMS) 区分开来.
- 产生的DMS具有不同的中断概率 (pd = 0.1,0.2,0.3).
- 人类性能 (d'值) 与使用序列特征的最佳贝叶斯模型进行了比较.
主要成果:
- 人类观察者的灵敏度 (d'值) 明显低于最佳贝叶斯观察者的灵敏度.
- 性能在不同的中断概率上有所不同.
- 探索了特定的序列特征,如最长的重复次序,作为潜在的决策依据.
结论:
- 人类纹理图案检测的灵敏度低于最佳模型.
- 观察者可能会依靠简化特征提取而不是整体序列分析.
- 一个模式特征池模型可以更好地解释人类在这个信号检测任务中的表现.
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