Fernandez Julian Martin, Farell Bart
Institute for Sensory Research, Syracuse University, Syracuse, New York 13244-5290, USA.
Neurocomputing (Amst). 2008 Mar;71(7-9):1629-1641. doi: 10.1016/j.neucom.2007.04.006.
We introduce a model for the computation of structure-from-motion based on the physiology of visual cortical areas MT and MST. The model assumes that the perception of depth from motion is related to the firing of a subset of MT neurons tuned to both velocity and disparity. The model's MT neurons are connected to each other laterally to form modulatory receptive-field surrounds that are gated by feedback connections from area MST. This allows the building up of a depth map from motion in area MT, even in absence of disparity in the input. Depth maps from motion and from stereo are combined by a weighted average at a final stage. The model's predictions for the interaction between motion and stereo cues agree with previous psychophysical data, both when the cues are consistent with each other or when they are contradictory. In particular, the model shows nonlinearities as a result of early interactions between motion and stereo before their depth maps are averaged. The two cues interact in a way that represents an alternative to the "modified weak fusion" model of depth-cue combination.
我们基于视觉皮层区域MT和MST的生理学原理,引入了一种用于计算基于运动的结构的模型。该模型假设,从运动中感知深度与MT神经元的一个子集的放电有关,这些神经元同时被调整到速度和视差。该模型的MT神经元相互横向连接,形成调制感受野周围区域,这些区域由来自MST区域的反馈连接进行门控。这使得即使在输入中没有视差的情况下,也能在MT区域从运动中构建深度图。在最后阶段,通过加权平均将来自运动和立体视觉的深度图进行组合。该模型对运动和立体视觉线索之间相互作用的预测与先前的心理物理学数据一致,无论是当线索相互一致还是相互矛盾时。特别是,该模型显示出在运动和立体视觉的深度图被平均之前,它们早期相互作用的结果呈现出非线性。这两种线索的相互作用方式代表了深度线索组合的“修正弱融合”模型的一种替代方案。