The Detection and Segmentation of Image Motion

对于人类和机器来说，一个基本的问题是从经常被噪声污染的感觉信息中检测和识别运动模式。 先前的研究已经表明，提高信噪比灵敏度的一种方法是将视野中不同位置的许多不同运动检测器的输出相加。 然而，这种方法的一个重要困难是如何决定哪些局部运动检测器应该被求和。 虽然以前的研究已经研究了简单的平行运动的情况下，在一个模式中的所有元素以相同的速度移动，我们的研究将考虑更复杂的运动，它是可能的模式旋转或扩大随着时间的推移。 我们还将研究其运动被限制在视野的有限区域内的运动物体的检测。 将进行一系列心理物理实验，以分离人类视觉系统能够科普这些情况的基本机制。 这些研究的基本范式是呈现一个移动的点的模式与一个重叠的点的模式。观察者需要判断运动模式的一些基本方面，例如它的形状或运动方向。 操纵干扰噪声的量以确定待判断的每个属性的人类表现的极限。 基于这些实验的结果，我们将尝试开发一个计算模型，可以模拟人类观察员在各种不同任务上的表现。

A fundamental problem for both human and machine is to detect and identify moving patterns from sensory information that is often contaminated by noise. Previous research has shown that one way of enhancing signal to noise sensitivity is to sum the outputs of many different motion detectors in different locations of the visual field. An important difficulty with this approach, however, is how to decide which local motion detectors should be summated. Whereas previous studies have examined the case of simple translatory motion where all elements in a pattern move at the same velocity, our research will consider more complicated motions in which it is possible for patterns to rotate or expand over time. We will also investigate the detection of camouflaged objects whose motions are confined to a limited region of the visual field. A series of psychophysical experiments will be performed to isolate the basic mechanisms by which the human visual system is able to cope with these situations. The basic paradigm of these studies is to present a pattern of moving dots with a superimposed pattern of scintillating dots. Observers are required to judge some basic aspect of the moving pattern, such as its shape or its direction of movement. The amount of scintillating noise is manipulated to determine the limits of human performance for each attribute to be judged. Based on the results of these experiments we will attempt to develop a computational model that can simulate the performance of human observers on a wide variety of different tasks.