Intrinsic Constraints: Local Affine Reconstruction from Multiple Image Signals

内在约束：从多个图像信号进行局部仿射重建

• 批准号: 0643234
• 负责人: Fulvio Domini
• 金额: $ 34.95万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-02-15 至 2013-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0643234&HistoricalAwards=false
• 关键词: Intrinsic; Constraints; Local; Affine; Reconstruction

Human observers perceive a three-dimensional world even though images on the retina are two-dimensional. How this can be done has been a classic problem in visual perception. Researchers have isolated a list of "depth cues", such as binocular disparity and retinal velocity, that might inform the visual system about the third dimension. Several models have been developed to explain how perception of the third dimension depends on each cue in isolation. However, what remains to be explained is how the visual system operates when several depth cues are simultaneously available in the retinal projections.With support of the National Science Foundation, Dr. Domini will test a new depth-cue processing model that differs from the current cue-combination model in two respects: (i) it computes relative but not absolute estimates of the third dimension of depth and (ii) rather than being formulated in terms of averaging the depth magnitudes recovered from each cue in isolation, its estimates are based on sophisticated statistical analyses of the multidimensional cue space. Experiments with human observers will determine whether the model accurately captures the phenomena of human visual perception, including both the successes and errors that that human vision shows. In addition to advancing our basic understanding of visual perception, the results of this research may aid the development of more effective computer vision principles that could be used in the design of robots.

尽管视网膜上的图像是二维的，但人类观察者感知的却是三维的世界。如何做到这一点一直是视觉感知领域的一个经典问题。研究人员已经分离出一系列“深度线索”，比如双眼视差和视网膜速度，这些线索可能会告诉视觉系统关于第三维度的信息。已经开发了几个模型来解释对第三维度的感知如何孤立地依赖于每个线索。然而，仍有待解释的是，当几个深度线索同时出现在视网膜投影中时，视觉系统是如何运作的。在美国国家科学基金会的支持下，多米尼博士将测试一种新的深度线索处理模型，它与目前的线索组合模型在两个方面有所不同：(i)它计算第三维度深度的相对估计，而不是绝对估计；（ii）它不是根据从每个线索中孤立恢复的深度大小的平均来制定的，它的估计是基于对多维线索空间的复杂统计分析。人类观察者的实验将决定该模型是否准确地捕捉到人类视觉感知的现象，包括人类视觉所显示的成功和错误。除了促进我们对视觉感知的基本理解之外，这项研究的结果可能有助于开发更有效的计算机视觉原理，这些原理可用于机器人的设计。