Fowlkes Charless C, Martin David R, Malik Jitendra
Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, CA 94720, USA.
J Vis. 2007 Jun 8;7(8):2. doi: 10.1167/7.8.2.
Figure-ground organization refers to the visual perception that a contour separating two regions belongs to one of the regions. Recent studies have found neural correlates of figure-ground assignment in V2 as early as 10-25 ms after response onset, providing strong support for the role of local bottom-up processing. How much information about figure-ground assignment is available from locally computed cues? Using a large collection of natural images, in which neighboring regions were assigned a figure-ground relation by human observers, we quantified the extent to which figural regions locally tend to be smaller, more convex, and lie below ground regions. Our results suggest that these Gestalt cues are ecologically valid, and we quantify their relative power. We have also developed a simple bottom-up computational model of figure-ground assignment that takes image contours as input. Using parameters fit to natural image statistics, the model is capable of matching human-level performance when scene context limited.
图形-背景组织是指一种视觉感知，即分隔两个区域的轮廓属于其中一个区域。最近的研究发现，早在反应开始后10 - 25毫秒，V2区域就存在图形-背景分配的神经关联，这为局部自下而上加工的作用提供了有力支持。从局部计算线索中可以获得多少关于图形-背景分配的信息？我们使用大量自然图像的集合，其中人类观察者为相邻区域分配了图形-背景关系，我们量化了图形区域在局部上倾向于更小、更凸且位于背景区域下方的程度。我们的结果表明，这些格式塔线索在生态学上是有效的，并且我们量化了它们的相对强度。我们还开发了一个简单的自下而上的图形-背景分配计算模型，该模型将图像轮廓作为输入。使用根据自然图像统计数据拟合的参数，当场景上下文有限时，该模型能够匹配人类水平的表现。
