Integration of elementary features in texture perception

纹理感知中基本特征的整合

• 批准号: 471755627
• 负责人: Professor Dr. Günter Meinhardt
• 金额: --
• 依托单位: Abteilung Methodenlehre und Statistik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/471755627?language=en
• 关键词: Integration; elementary; features; texture; perception

Feature integration and its role in figure-ground segregation is a key problem of visual perception. According to established views, early retinotopic stages (V1, V2) serve local feature analysis, while shape detection and object recognition are located at higher ventral areas, which process objects in a feature and view independent manner. In line with an early channeling – later integration account strong cue combination effects (“synergy”) among orientation and spatial frequency were found. Texture shapes were much better detectable in Gabor random fields when there was feature contrast in both orientation and spatial frequency, however, only when they were barely visible by one feature alone and only when the Gabor elements formed a definite 2D shape. EEG recordings revealed a long-lasting negative potential starting at 130 ms specific for double-cue targets at electrodes around the inferior temporal region (TP), while there currently is no unique evidence for a double-cue correlate at central occipital (OZ) electrodes, suggesting feature integration at later shape-processing areas. Recently, the synergy effect was revisited using bandwidth modulated textures. Authors found that a low-level summary statistic, net contrast energy, computed from multiple scales and orientations, explains the synergy effect. The findings challenge a late, shape-based account of feature integration. In this project we readdress the origin of the feature synergy effect for the essential features of spatial luminance distributions in a Fourier sense (orientation, spatial scale and luminance) in texture perception. First, we try to establish that the strong cue combination effects in texture figure detection are fully captured by local energy computations. Second, we disentangle texture figure detection from shape discrimination with dedicated experimental designs, and explore whether the cue summation schemes found in shape identification tasks differ from the rules found in detection tasks. Third, EEG recordings will be analyzed by source modeling techniques to distinguish between activity originating in the primary visual cortex and the ventral processing stream. Applied with dedicated designs and tasks which disentangle detection and shape discrimination this will shed light on the time-course and neural correlates of cue summation in the two major processing regions for textures and shapes.

特征整合及其在图地分离中的作用是视觉感知中的一个关键问题。根据已有观点，视网膜早期阶段（V1、V2）服务于局部特征分析，而形状检测和物体识别位于较高的腹侧区域，以特征和视图独立的方式处理物体。在取向和空间频率之间发现了强烈的线索组合效应（“协同效应”），这与早期的渠道-后期的整合解释一致。当纹理形状在方向和空间频率上都有特征对比时，在Gabor随机场中可以更好地检测到纹理形状，然而，只有当它们仅被一个特征几乎看不到时，并且只有当Gabor元素形成明确的二维形状时。脑电图记录显示，下颞区（TP）周围电极上的双线索目标在130 ms时开始出现持久的负电位，而目前没有独特的证据表明双线索在中央枕区（OZ）电极上相关，这表明在后期形状处理区域存在特征整合。最近，使用带宽调制纹理重新审视了协同效应。作者发现，从多个尺度和方向计算的低水平汇总统计，净对比能，解释了协同效应。这些发现挑战了最近基于形状的特征整合理论。在这个项目中，我们重新解决了纹理感知中傅里叶意义上空间亮度分布的基本特征（方向、空间尺度和亮度）的特征协同效应的起源。首先，我们试图通过局部能量计算来充分捕捉纹理图像检测中的强线索组合效应。其次，我们通过专门的实验设计将纹理图像检测与形状识别分离开来，并探讨形状识别任务中的线索和方案是否与检测任务中的规则不同。第三，脑电图记录将通过源建模技术进行分析，以区分源自初级视觉皮层和腹侧处理流的活动。应用于分离检测和形状识别的专用设计和任务，将揭示纹理和形状两个主要处理区域线索求和的时间过程和神经关联。