Hierarchical motion perception as causal inference.

Sabyasachi Shivkumar, Gregory C DeAngelis, Ralf M Haefner
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Abstract

Since motion can only be defined relative to a reference frame, which reference frame guides perception? A century of psychophysical studies has produced conflicting evidence: retinotopic, egocentric, world-centric, or even object-centric. We introduce a hierarchical Bayesian model mapping retinal velocities to perceived velocities. Our model mirrors the structure in the world, in which visual elements move within causally connected reference frames. Friction renders velocities in these reference frames mostly stationary, formalized by an additional delta component (at zero) in the prior. Inverting this model automatically segments visual inputs into groups, groups into supergroups, etc. and "perceives" motion in the appropriate reference frame. Critical model predictions are supported by two new experiments, and fitting our model to the data allows us to infer the subjective set of reference frames used by individual observers. Our model provides a quantitative normative justification for key Gestalt principles providing inspiration for building better models of visual processing in general.

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层次运动知觉作为因果推理。
既然运动只能相对于一个参考系来定义,那么哪个参考系指导感知呢?一个世纪的心理物理学研究产生了相互矛盾的证据:视网膜中心、自我中心、世界中心,甚至是客体中心。我们引入了一个层次贝叶斯模型,将视网膜速度映射到感知速度。我们的模型反映了世界的结构,其中视觉元素在因果关联的参考框架内移动。摩擦使得这些参考系中的速度大多是静止的,在先前的参考系中有一个额外的δ分量(在零处)。反过来,这个模型会自动将视觉输入分成组,组分成超组等,并在适当的参考框架中“感知”运动。两个新的实验支持了关键的模型预测,将我们的模型拟合到数据中使我们能够推断出个体观察者使用的主观参考框架集。我们的模型为格式塔的关键原则提供了定量的规范性论证,为建立更好的视觉处理模型提供了灵感。
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