Colas Francis, Droulez Jacques, Wexler Mark, Bessière Pierre
LPPA, Collège de France, 11, place Marcelin Berthelot, 75231 Paris Cedex 05, France.
Biol Cybern. 2007 Dec;97(5-6):461-77. doi: 10.1007/s00422-007-0183-z. Epub 2007 Nov 7.
Human observers can perceive the three- dimensional (3-D) structure of their environment using various cues, an important one of which is optic flow. The motion of any point's projection on the retina depends both on the point's movement in space and on its distance from the eye. Therefore, retinal motion can be used to extract the 3-D structure of the environment and the shape of objects, in a process known as structure-from-motion (SFM). However, because many combinations of 3-D structure and motion can lead to the same optic flow, SFM is an ill-posed inverse problem. The rigidity hypothesis is a constraint supposed to formally solve the SFM problem and to account for human performance. Recently, however, a number of psychophysical results, with both moving and stationary human observers, have shown that the rigidity hypothesis alone cannot account for human performance in SFM tasks, but no model is known to account for the new results. Here, we construct a Bayesian model of SFM based mainly on one new hypothesis, that of stationarity, coupled with the rigidity hypothesis. The predictions of the model, calculated using a new and powerful methodology called Bayesian programming, account for a wide variety of experimental findings.
人类观察者可以利用各种线索感知其周围环境的三维（3-D）结构，其中一个重要线索是光流。视网膜上任何一点投影的运动既取决于该点在空间中的移动，也取决于它与眼睛的距离。因此，视网膜运动可用于在一个称为“从运动中提取结构”（SFM）的过程中提取环境的三维结构和物体的形状。然而，由于三维结构和运动的许多组合都可能导致相同的光流，SFM是一个不适定的逆问题。刚性假设是一种约束，旨在正式解决SFM问题并解释人类的表现。然而，最近，一些针对移动和静止人类观察者的心理物理学结果表明，仅刚性假设无法解释人类在SFM任务中的表现，但目前还没有已知的模型能够解释这些新结果。在此，我们主要基于一个新假设——平稳性假设，并结合刚性假设，构建了一个SFM的贝叶斯模型。该模型使用一种称为贝叶斯编程的新的强大方法计算得出的预测，解释了各种各样的实验结果。
